Generative AI, which refers to artificial intelligence systems that can generate new content based on learned patterns and data, has transformative potential across a wide range of industries. Here’s a deeper look into how this technology can be applied in healthcare, entertainment, and design:

Healthcare

1. Drug Discovery and Development:

Generative AI can accelerate the drug discovery process by predicting molecular behavior and generating new compounds that might be effective against specific diseases. This reduces the time and cost associated with traditional drug discovery methods.

2. Personalized Medicine:

AI models can generate personalized treatment plans by analyzing patient data, including genetic information, lifestyle, and previous health records. This can lead to more effective and tailored treatments for individual patients.

3. Medical Imaging:

AI can enhance image analysis in radiology and pathology. Generative models can improve the clarity of medical images, generate synthetic data for training purposes, and even help in reconstructing missing or corrupted data.

4. Prosthetics and Implants Design:

AI can assist in designing custom prosthetics and implants by generating models that perfectly fit the unique anatomical structure of patients. This can improve comfort and functionality for the user.

Entertainment

1. Content Creation:

In film, music, and gaming, generative AI can create new scripts, compose music, or develop new gaming environments and scenarios. This can lead to more innovative and engaging content.

2. Virtual Reality and Augmented Reality:

AI can generate immersive environments that are indistinguishable from real life, enhancing the user experience in VR and AR applications. This technology can create dynamic scenarios that react to the user’s actions in real-time.

3. Animation and Visual Effects:

Generative AI can automate part of the animation process, creating realistic and complex animations that would be time-consuming and costly to produce manually. It can also be used to enhance visual effects in movies and video games.

Design

1. Architectural and Industrial Design:

AI can help designers by generating multiple design alternatives based on specific criteria like space utilization, energy efficiency, or aesthetic preferences. This allows designers to explore more options and optimize designs more efficiently.

2. Fashion and Textile Design:

In fashion, AI can predict trends and generate new designs based on past styles, current trends, and emerging preferences. It can also help in creating custom clothing by generating patterns and designs that fit individual customers.

3. User Experience (UX) and Interface Design:

AI can generate design elements that are optimized for usability and aesthetic value, helping UX designers create more effective interfaces. It can also simulate user interactions to predict how changes to the design will impact user experience.

Cross-Industry Applications

1. Automation of Creative Processes:

Across industries, generative AI can automate repetitive and time-consuming tasks, allowing humans to focus on more strategic and creative aspects of their work.

2. Enhanced Decision Making:

By generating forecasts, scenarios, and models, AI can aid in complex decision-making processes, providing insights that might not be apparent through traditional methods.

3. Training and Simulation:

Generative AI can create realistic scenarios for training purposes across various fields, from piloting aircraft to medical surgery simulations, enhancing the learning experience without the associated risks of real-world training.

Generative AI’s ability to analyze vast amounts of data and generate insightful outputs makes it a powerful tool in these and many other industries, potentially leading to innovations that can transform the way we live and work.

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A case of machine learning in healthcare shows that algorithms and liquid metal could lead to the development of prosthetic hands having the ability to feel objects.

By using machine learning in healthcare, researchers from Florida Atlantic University’s College of Engineering and Computer Science and collaborators are creating prosthetic hands that can “feel” by incorporating stretchable tactile sensors using liquid metal on the fingertips.

“Encapsulated within silicone-based elastomers, this technology provides key advantages over traditional sensors, including high conductivity, compliance, flexibility and stretchability. This hierarchical multi-finger tactile sensation integration could provide a higher level of intelligence for artificial hands,” the press release stated.

Each fingertip has more than 3,000 touch receptors that respond to pressure. The sensation felt in the fingertips is what humans rely on to manipulate objects. Individuals with upper limb amputations face a unique challenge without that pressured sense of touch.

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Although there are several high-tech, dexterous prosthetics available, the ability to have a sense of touch is still lacking. The absence of sensory feedback often results in objects being dropped or crushed by prosthetic hands.

For the study, researchers used individual fingertips on the prosthetic hand to differentiate between various speeds of a sliding motion along four different textured surfaces. The textures had one variable parameter: the distance between the ridges. In order to detect the textures and speeds, researchers trained four machine learning algorithms.

There were 20 trials conducted on each of the 10 surfaces. These were used to see if the machine learning algorithms could distinguish between the ten different complex surfaces made up of randomly generated permutations of four different textures.

The result revealed that the tactile information from the liquid metal sensors were able to differentiate between the multi-textured surfaces, demonstrating a new form of hierarchical intelligence. Additionally, the machine learning algorithms were able to distinguish between all the speeds with high accuracy.

“Significant research has been done on tactile sensors for artificial hands, but there is still a need for advances in lightweight, low-cost, robust multimodal tactile sensors,” Erik Engeberg, PhD, senior author, an associate professor in the Department of Ocean and Mechanical Engineering said in a press release.

“The tactile information from all the individual fingertips in our study provided the foundation for a higher hand-level of perception enabling the distinction between ten complex, multi-textured surfaces that would not have been possible using purely local information from an individual fingertip,” Engeberg continued.

“We believe that these tactile details could be useful in the future to afford a more realistic experience for prosthetic hand users through an advanced haptic display, which could enrich the amputee-prosthesis interface and prevent amputees from abandoning their prosthetic hand.”

The team of researchers compared the four different machine learning algorithms for their successful classification abilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). 

The time-frequency features of the liquid metal sensors were removed to train and test the machine learning algorithms. The NN seemed to perform the best with 99.2 percent accuracy with speed and texture detection.

“The loss of an upper limb can be a daunting challenge for an individual who is trying to seamlessly engage in regular activities,” Stella Batalama, PhD, dean, College of Engineering and Computer Science said in a press release.

“Although advances in prosthetic limbs have been beneficial and allow amputees to better perform their daily duties, they do not provide them with sensory information such as touch. They also don’t enable them to control the prosthetic limb naturally with their minds,” Batalama continued.

“With this latest technology from our research team, we are one step closer to providing people all over the world with a more natural prosthetic device that can ‘feel’ and respond to its environment.”

Researchers believe that this artificial intelligence technology can improve the control of prosthetic hands and the lives of those who need them.

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How does cloud computing lead to improved healthcare outcomes?

The Healthcare industry is one of the fastest-growing sectors with a CAGR of 5% from 2019 to 2023. This is due to issues like the spread of chronic diseases, the aging population, and more. In the healthcare industry, a huge amount of data is created on a daily basis. Therefore, there is a need for the creation, storage, usage, and sharing of healthcare data. This caters to the need for cloud computing for quick, cost-effective and safe, and secure solutions.

Cloud computing to be precise, is the delivery of computing services (such as servers, networking, databases, analytics, intelligence, and storage) over the cloud (internet) to provide flexible resources, economies of scale, and faster innovation. Cloud computing helps in reducing operating costs, running infrastructure more effectively, etc. Thus, cloud computing enables the healthcare industry to break free from limitations while offering better patient outcomes.

Shifting to the cloud computing service is advantageous for both healthcare providers as well as for patients. The healthcare cloud computing trend is expected to grow to 64.7 billion US dollars by 2025.

Cloud Computing in Healthcare Sectors

Cloud computing assists healthcare providers in reducing operational expenses while providing improved, personalized care. Also, it helps to drive efficient workflows thus leading to better service. Parallel to this, cloud computing helps the patients to receive quick responses from the healthcare industry and also helps them to keep track of their health better through healthcare data offered by cloud solutions.

Healthcare providers and hospitals across the globe are increasing the application of cloud computing to solve problems like care coordination, data security, and population health.

Advanced cloud computing allows medical research innovation by helping researchers access important data sets under solid control. Cloud has also proved a powerful tool in hospital settings.

Advanced compute, storage capability, and database, combined with artificial intelligence and machine learning tools help the healthcare industry in building solutions and providing services to the patients. Innovative cloud computing technology will serve to equal access to care, enable the healthcare provider to make the best decision, and also access to significant medical research.

Enhanced database capabilities and advanced computing power are making preventative population health analysis a reality.

How does Cloud Computing lead to improved healthcare outcomes?

Cost Reduction

The basic theory of cloud computing is the availability of computer services like data storage and computing power. Therefore, this frees the hospitals and healthcare providers from the purchase of hardware and servers for storage. There are no charges kindred with cloud storage of data. The healthcare industry can only pay for the resources they use and thus results in huge cost savings. Cloud computing also offers an efficient environment for scaling which is highly desirable by healthcare providers for improved healthcare service.

Easy Interoperability

Cloud computing helps in establishing data combinations (irrespective of the point of origin or storage) throughout the healthcare system. This process is called Interoperability. As a result of interoperability data of the patients become easily available for distribution. This helps in gaining visions to advance healthcare planning and delivery. Thus, cloud computing enables healthcare providers to get easy access to the patient data collected from various sources and provide prescriptions and treatment protocols on time.

Approach to high powered analytics

The Healthcare industry contains data that are both structured as well as unstructured. Cloud helps in collecting and collating important data of the patients from different sources. With the modern computing power of the cloud, the processing of large datasets becomes more viable. The application of Big Data analytics and Artificial Intelligence on patient data also paves the way for developing more advanced care plans for patients.

Patient’s access to data

Cloud computing allows patients to get control over their own health. Cloud computing makes it accessible for the patients to get hold of their data from the cloud and this leads to patient participation in making decisions of their own health.

Telemedicine Capabilities

Cloud storage of data offers remote accessibility of data. The integration of cloud computing with the healthcare industry carries the ability to improve a number of healthcare-related functions such as telemedicine, virtual medication, and post-hospitalization care plans. Telemedicine apps add the element of convenience to healthcare delivery while upgrading the patient experience. Cloud-based telehealth systems and applications allow easy sharing of healthcare data, improve accessibility and provide healthcare coverage to the patients during the preventative, treatment as well as recovery phase.

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Artificial intelligence (AI) has proven to have several benefits across different industries and businesses. One sector that has benefitted from the use of AI is the healthcare industry. This sector is always full of patient information, health records, and other important data crucial to patients and hospitals. 

Major problems facing healthcare data are cyberattacks, losing the information, and improper handling, leading to mixing up the records. These mistakes always have devastating effects on the healthcare sector as these medical procedures and other treatments are dependent on these data. In addition, there are other procedures outside the health industry that are dependent on these data. Therefore, properly managing healthcare data is fundamental in the healthcare industry.

The importance of these data has led to the adoption of AI in hospitals to help in the management. Here are some of the applications of AI in optimizing data management: 

• Convenient Data Transmission

Health records are constantly subjected to several transfers among patients, hospitals, remote workers, and other legally entitled parties. When transferring this data, there needs to be a convenient and streamlined way to reach all the desired recipients in time. For example, you may opt to use faxing services, like MyFax, and several others to send the faxes digitally without the need for printing and scanning. 

These modes of data transmission ensure that the records are sent faster and securely. This helps reduce cases of alterations or sending to wrong addresses. With AI, the sharing of information is simplified.

• Data Security 

Several cyberattacks are lodged on these records during these transfers as criminals try to steal or change the records. These attacks are a major concern for the healthcare sector. 

Moreover, even when being stored, patient information is always vulnerable to attacks from hackers. Covering all these attack points manually could be next to impossible, considering the amount of data being held by the information system. 

However, with the application of AI, securing health records against any cyberattacks is promising and fruitful. This is because AI can identify possible entry points for hackers and provide possible solutions for correcting them. Moreover, AI can diagnose the system to identify and correct bugs that would otherwise affect the data management system. 

• Automation Of Data Flow

When patients enter a medical facility, their records are always taken by the hospital from time to time. Each process of their treatment is dependent on the information from the previous step to avoid any cases of errors. The number of patients in the hospital could be challenging to handle if the data flow is done manually. Moreover, handling data manually can lead to confusion.

In contrast, AI automates the data flow from one point to the other, streamlining the whole process. Once the information is entered at the first stage, it becomes accessible for authorized personnel in the hospitals. These records are always entered against a patient’s identity, which means very minimal cases of errors. It also becomes easy for return patients to continue their treatment as the complete information is already recorded in the system. 

• Optimizing Data Storage

Traditionally, health records could be stored in paper works and filed for future references. However, this storage has several disadvantages and limitations. 

First, once a record is added, deleting or changing is difficult unless new paperwork is filed. Secondly, paper is limited in storage, and very little information can be stored on a piece of paper. Finally, once you lost these records, it would be difficult to retrieve them due to a lack of backups.

Fortunately, AI changes all these and optimize data storage in many ways. For example, cloud storage can help hospitals store large quantities of data in only one system. In addition, these cloud services have data backup where you can retrieve any lost information. It’s also possible to change any medical data without altering the other record elements when storing it in a system.

• Data Analysis And Decision Making 

Another important use of AI when handling health data, especially in big data, is analyzing and interpreting the data. With AI, it’s possible to deduce important data points from health records, analyze them, and then present them to understand the chart. This can help in decision-making regarding medical procedures or genetic mapping for patients.

Conclusion 

The healthcare sector is crucial due to the information stored in the systems and their value. Therefore, there’s the need to have an efficient data management system that can ensure information security and streamline any process that depends on these data. 

Manual handling of these data has some limitations, unlike AI, which has several applications in health data management. It can be used in automating data flow and aiding in crucial decision making among many others. It’s safe to say that the application of AI in healthcare will improve. 

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Healthcare Industry Leverages Artificial Intelligence

With the continuous evolvement of Artificial Intelligence, the world is being benefited to the utmost level, as the applications of Artificial Intelligence is unremitting. This technology can be operated in any sector of industry, including the healthcare industry.The advancement of technology and the AI (Artificial Intelligence), as a part of modern technology have resulted in the formation of a digital macrocosm. Artificial Intelligence, to be precise, is a programming where, there is a duplication of human intelligence incorporated in the machines and it works and acts like a human.

Artificial Intelligence is  transmuting the system and methods of the healthcare industries. Artificial Intelligence and healthcare, were found together over half a century. The healthcare industries use Natural Language Process to categorise certain data patterns.Natural Language Process is the process of giving a computer, the ability to understand text and spoken words just like the same way human beings can. In the healthcare sector, it gives the effect to the clinical decision support. The natural language process uses algorithms that can mimic like human responses to conversation and queries. This NLP, just like a human can take the form of simulated mediator using algorithms to connect to the health plan members.

Artificial Intelligence can be used by the clinical trials, to hasten the searches and validation of medical coding. This can help reduce the time to start, improve and accomplish clinical trainings. In simple words medical coding is transmitting medial data about a patient into alphanumeric code.

How Artificial Intelligence Accelerates in the Healthcare Industry?

Clinical Decisions– All the healthcare sectors are overwhelmed with gigantic volumes of growing responsibility and health data. Machine learning technologies as a part of Artificial Intelligence, can be applied to the electronic health records, with the help of this the clinical professionals can hunt for proper, error-free, confirmation-based statistics that has been cured by medical professionals. Further, Natural Language Process just like the chatbots, can be used for everyday conversation where it allows the users to type questions as if they are questioning a medical professional and receive fast and unfailing answers.

Health Equity– Artificial Intelligence and Machine learning algorithms can be used to reduce bias in this sector by promoting diversities and transparency in data to help in the improvement of health equity.

Medication Detection– Artificial Intelligence can be used by the pharma companies, to deal with drug discoveries and thus helping in reducing the time to determine and taking drugs all the way to the market.  Machine Learning and Big Data as a part of Artificial Intelligence do have the great prospective to cut down the value of new medications.

Pain Management– With the help of Artificial Intelligence and by creating replicated veracities the patients can be easily distracted from their existing cause of pain. Not only this, the AI can also be incorporated for the for the help of narcotic crisis.

System Networked Infirmaries– Unlike now, one big hospital curing all kind of diseases can be divided into smaller pivots and spokes, where all these small and big clinics will be connected to a single digital framework. With the help of AI, it can be easy to spot patients who are at risk of deterioration.

Medical Images and Diagnosis– The Artificial Intelligence alongside medical coding can go through the images and X-rays of the body to identify the system of the diseases that is to be treated.  Further Artificial Intelligence technology with the help of electronic health records is used in healthcare industry that allows the cardiologists to recognize critical cases first and give diagnosis with accuracy and potentially avoiding errors.

Health Record Analysing– With the advance of Artificial Intelligence, now it is easy for the patients as well as doctors to collect everyday health data. All the smart watches that help to calculate heart rates are the best example of this technology.

This is just the beginning of Artificial Intelligence in the healthcare industry. Making a start from Natural Language process, Algorithms and medical coding, imaging and diagnosis, there is a long way for the Artificial Intelligence to be capable of innumerable activities and to help medical professionals in making superior decisions. The healthcare industry is now focusing on technological innovation in serving to its patients. The Artificial Intelligence have highly transmuted the healthcare industry, thus resulting in development in patient care.

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Technology then and now in Healthcare.

The pandemic has been the best accelerator of innovative technological implementations in the healthcare industry. Rightfully, the healthcare industry is now thriving on modern technological developments.

Few high-end technologies that are now the crucial slices of a healthcare unit are beacon gadgets for crowd management while machine learning devices are deployed to yield appropriate disease detection and treatment methodologies. Such adoption of innovative technologies has helped medical professionals to devote more time to value-added activities like strategizing on the enhancement of patient care.

Technology will Shape the Future of Healthcare

Technology, in healthcare, is progressing along with transforming medical conducts as a whole. Such a phenomenon has struck health experts with a fresh perspective that can be leveraged for improving the healthcare profession.

Precisely, technology innovation is shaping the healthcare industry, making it sustainable. Technology in healthcare will generate a cost-effective and efficient health infrastructure.

A Glimpse of the Current Medical Landscape of India

The past five years have been very crucial and significant for the transformation of the healthcare sector. The transformation involves upgrading diagnostic tools, ventilators, medical, and surgical devices. Such transformations have resulted in positive outcomes.

A relevant example of technological transformation is ATMAN AI. ATMAN AI is an AI-powered tool used to detect complicated side effects of Covid-19 and heart diseases. This development was aimed at rural residents and residents living on the outskirts. Such a development meticulously contributed to reshaping the health infrastructure in socially backward areas, ensuring health equity for all.

Additionally, specialized surgical innovation that is inclusive of high-end technology and research has also evolved over the last two decades.

What Does Technological Transformation Mean for Healthcare System in India?

The healthcare system in India is often doubted and brought under question. The primary reason of which can be lack of skilled medical professionals and overwhelm of traditional medical conducts. There are about 500 surgeons who are adept in robotic-assisted surgeries (RAS).

Economists have pointed out the need to speed up technology adoption by the healthcare systems in India. Increased adoption of technology and proper training of the human workforce to operate disruptive technology incorporations can elevate the status of the Indian healthcare system, giving rise to more equity in healthcare opportunity dissemination.

Technological Adoption: Quick Stats

In 2021 around 8 hospitals out of 10 from all across the globe have faith in results yielded by AI-powered tools. Around 76% of healthcare professionals in India use machine learning tools and gadgets that are driven digitally.

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Artificial intelligence applications support doctors’ diagnostic decisions, automate certain tasks, says Turkish social media expert

ANKARA

A Turkish social media expert said artificial intelligence (AI) brings a new vision to the healthcare sector.

“Artificial intelligence brings revolutionary developments in the field of health, as in all areas of life,” Deniz Unay told Anadolu Agency.

“Machine learning and assisted artificial intelligence have features that can develop an entire health system within the framework of a new vision,” Unay said.

Unay said the AI applications support doctors’ diagnostic decisions and automate certain tasks underlining AI’s rise in healthcare applications.

AI can help better and more accurate detection of symptoms, analyzing the side effects of treatments, and processing large amounts of data produced by healthcare facilities, he said.

However, AI in the medical field is an area that is not yet fully sufficient and is considered to be developed especially for automated robotic surgery applications, he warned.

“Artificial intelligence software and robots, which will assist doctors in many areas, enable faster and safer health services,” he said, adding that AI developments in medicine are planned to be used widely on both general health practices and drugs.

Everyone in the field of health, from specialist doctors to first-aid workers, will start to benefit from artificial intelligence technology soon, he added.

The revenue from AI systems in healthcare worldwide in 2021 exceeded $6.6 billion, according to data from Germany-based statistics company Statista.

The investment amount is expected to increase significantly in line with the increasing desire to use artificial intelligence and robots in the health sector, he said, adding that the increase will lead to easier use of health services by large groups.

“Great importance is given to the use of artificial intelligence in the health sector to spread health services to wider areas. Health services offered in various regions are expected to increase, especially with the technological infrastructure,” he continued.

With the spread of medical instruments, doctors are forced to consider more data, he added.

He went on to say that AI is mostly used in medical imaging and interpretation of radiology.

Underlining that some cancers, such as lung or breast cancer, are tough to identify in images produced by scanners, he said programs can identify abnormalities that cannot be detected with the naked eye to detect early tumors more reliably and target better treatments.

Until recently, AI in healthcare was limited to research or predictive analytics, he said. Much focus is now on developing technologies that can improve robot-assisted surgery, he added.

“There are already significant uses of artificial intelligence that prove how it can improve the techniques used for several years in the field of robotic surgery, especially in the field of microsurgery,” Unay noted.

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AI in healthcare is growing multifold, from diagnostics to pain management

Artificial Intelligence has been playing a growing role in the world in the last few decades. What most don’t understand is artificial intelligence introduces itself in numerous structures that sway everyday life. Signing into your social media, email, car ride services, and online shopping platforms, etc. all include artificial intelligence algorithms to improve customer experience. AI in healthcare is growing quickly; explicitly, in diagnostics and treatment management.

As of late, AI applications in healthcare have sent huge waves across medical services, fuelling a conversation of whether AI doctors will in the end supplant human doctors in the future. However, experts believe that human doctors won’t be supplanted by machines soon, yet the use of artificial intelligence in healthcare can help doctors to settle on better clinical choices or even supplant human judgment in certain functional areas of healthcare.

One emerging application of AI in healthcare is a new study led by the research team of Northwestern University faculty and alumni, created and applied artificial intelligence, or machine learning algorithms to physiological information — including respiratory rate, oxygen levels, pulse rate, body temperature, blood pressure, etc. from patients with chronic pain suffering sickle cell illness. Not exclusively did the scientists’ methodology beat baseline models to gauge subjective pain levels, it additionally distinguished changes in pain and abnormal pain fluctuations.

The team of researchers utilized data from 46 adults and kids with sickle cell sickness over a consolidated total of 105 hospital stays, taking a look at the physiological information alongside patient-reported pain scores to create models that could derive pain levels and identify changes in pain level through machine learning

Presently, patients should evaluate their pain on a scale of zero to 10. This can be a troublesome assignment on the grounds that numerous individuals experience pain in an unexpected way, and little kids and unconscious patients can’t rate their pain by any means. The scientists say that these subjective evaluations of pain could be enhanced with a more objective, less intrusive, data-driven approach to help physicians with a more accurate treatment plan.

The researchers then analyzed their new models against existing ones that attempt to evaluate levels of pain but that don’t use physiological estimations. The new models outflanked the current ones.

According to Daniel Abrams at Northwestern University in Illinois, “The big picture is that we want to better understand how people experience pain. We’re hoping that the long-term outcome of this line of research is a more quantitative approach to pain management.”

Prior to this use of AI in pain management, Professor Jeff Hughes, Chief Scientific Officer at PainChek, clarifies how smart automation and AI in healthcare can reform pain assessment in patients with dementia who find it very difficult to communicate.

PainChek was created as a compelling solution for this issue. Its novel blend of automated facial-analysis technology and smart automation empowers care takers and healthcare experts to look for the presence of pain when it isn’t self-evident, to evaluate the intensity of pain and screen the effect of treatment to optimize and witness the overall quality of care.

This information is then integrated with non-facial features seen by the application user and information through a range of digital checklists, which together permits automatic calculation of a total pain score and the task of a pain intensity level.

There are different impacts of AI in healthcare. Commonly, AI used in healthcare leverages a web data set permitting doctors and experts to access a lot of diagnostic resources. As doctors are profoundly knowledgeable in their field and are up-to-date with present research, AI technology in healthcare incredibly builds a quicker result that can be matched with their clinical knowledge.

Nonetheless, artificial intelligence in healthcare presents numerous apprehensions as discussed, particularly in the clinical setting, of in the long-run substituting or lowering down the requirement for human doctors. In any case, so much research and data have shown that it is almost certain that AI in healthcare will benefit and improve clinical diagnostics and decision making as opposed to lessen clinician need.

The opportunities for AI applications in healthcare from emergency clinics and primary care, to home care, are huge. The use of artificial intelligence in healthcare can automate patient assessment and eliminate assessor bias. It can assess patient risk, for example, of a patient building up a specific disease, analyze illness, for instance, by deciphering ECG results and X-ray pictures, select the ideal treatment dependent on a patient’s clinical history and the results of clinical trials, and monitor disease and recognize early warning signs of deterioration.

The use of AI in healthcare will be driven by the availability of big data on which to train predictive algorithms, which help (instead of supplanting) human doctors, encourage curiosity-based reasoning, empower collaboration and eliminate unremarkable tasks, thus, improving patient care.

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Telehealth and virtual consults are changing how medical care is delivered. Artificial intelligence is integral to improving these experiences for both the doctor and the patient

The telehealth and healthcare IT market has been growing in recent years, and it is expected to hit $390 billion by 2024. The 2020 coronavirus pandemic has driven the need for remote healthcare services even further, with most countries implementing restrictions that encourage the public to stay at home. In May 2020, McKinsey & Company reported that healthcare providers are seeing 50 to 175 times the number of patients via virtual consultations than they did before the pandemic took effect. 

But telehealth is not just a symptom of necessity. Aside from patient and doctor safety, telehealth can also have long-term positive effects on patient well-being. By avoiding the logistical challenges and inconvenience associated with in-person visits, patients can better manage chronic conditions, medications, and lifestyle. 

However, the inherent complexity of healthcare regulations and administrative tasks have given telehealth a bad reputation. The traditional one-to-one conversation between patient and doctor has been tarnished through the computer screen with the constant background noise of keyboard clicks as medical personnel try to navigate their many digital systems and regulatory mandates, all while trying to listen to their patients and offer expertise. The result is a de-personalised patient experience and physician burnout. 

At Nuance, we are using innovative artificial intelligence-powered solutions to remove these administrative burdens from clinicians, provide better patient experiences, and strengthen the doctor-patient relationship. 

For example, earlier this year, we announced the integration of our ambient clinical intelligence (ACI) solution, the Nuance Dragon Ambient eXperience (DAX), with Microsoft Teams. Hosted on Microsoft Azure, the Nuance DAX and Teams integration can improve virtual telehealth consultations by enabling physicians to use Nuance DAX within their familiar Teams workflows. As a result, they can focus on the patient while the AI captures the details of the virtual visit, creating clinical documentation that writes itself. The solution incorporates patient data securely with contextual information from electronic health records to automatically populate a complete clinical note within the patient’s medical record. 

We are already hearing how AI helps doctors spend more time with their patients, listening to their concerns and questions. At Cooper University Health Care in New Jersey, USA, doctors are using Nuance DAX to focus on caring for patients. Medical director Snehal Gandhi said, “By capturing every word of the physician-patient encounter and automatically generating the clinical note, Nuance DAX frees physicians to focus more on interacting with their patient rather than documentation, which improves the overall experience for both patient and physician.” 

The world is evolving, and with it is the nature of healthcare and patient expectations. Digital technologies such as AI will continue to play an integral role in how healthcare providers deliver care to their patients. 

Diana Nole is the executive vice president and general manager of healthcare at Nuance Communications

This article was originally published in the Winter 2020 issue of The Record. To get future issues delivered directly to your inbox, sign up for a free subscription.

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Healthcare artificial intelligence awareness and adoption has increased significantly in the past year, with familiarity rising among hospital executives.

Nine in ten hospitals now have an artificial intelligence strategy in place, and 75 percent of healthcare executives believe AI initiatives are more critical now because of the pandemic, according to a report from Sage Growth Partners.

These results show a significant increase from 2019, when 47 percent had no AI or automation plan in place.

Of the 90 percent of hospitals with an AI strategy, the report showed that 41 percent of organizations are still in the planning stage, while 25 percent are in the early implementation stage.

Dig Deeper

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Additionally, the report noted that from 2019 to 2020, executive familiarity with automation grew from 50 percent to 66 percent and deployment of automation solutions increased from 23 percent to 34 percent.

Given that most healthcare executives have an AI and automation strategies in place, researchers expect that the use of this technology will grow significantly in the next two years.

“It’s incredibly promising to see the continued and growing adoption of AI within healthcare,” said Sean Lane, CEO of Olive.

“AI solutions are essential pieces of infrastructure at hospitals and health systems, and we have just begun to scratch the surface. There are so many more connections to make using AI– so many more lights to shine on all of the broken healthcare processes that stand between providers and patient care.”

The pandemic has also pushed hospital executives to increasingly rely on AI and automation. Seventy-six percent of respondents said automation has elevated in importance because cutting wasteful spending will help them recuperate and grow faster.

These findings echo those of a November 2020 survey, which showed that 56 percent of healthcare executives said that their response to COVID-19 has caused them to accelerate or expand their AI implementation strategies. The same survey found that 51 percent believe they’ll achieve a return on AI investments faster because of their pandemic response.

In the report from Sage Growth Partners, most respondents who have implemented automation solutions pointed out that the technology is live in only a few areas of their organization.

Among those with existing automation, 59 percent currently use it for five or fewer use cases. Executives also named revenue cycle management, supply chain, and clinical administration as the areas that would benefit most from automation.

Additionally, the executives stated that several barriers still exist to scaling AI and automation. Respondents noted that slow time to implement, lower ROI than expected, and staff constraints are the top challenges to implementation.

Executives also named key criteria for AI and automation success, including selecting the right partner.

“Given that automation is increasingly necessary but difficult to implement and scale, not all organizations will succeed. As several executives noted when interviewed, poorly executed automation can even set the organization back and make driving organizational buy-in for future automation projects more difficult. That makes having the right partner all the more important,” researchers stated.

According to respondents, the top criteria for selecting an automation partner are security and compliance, proven ROI, healthcare expertise, and reliable performance. Healthcare executives also largely prefer a healthcare-focused solution over one spread across multiple industries, with 66 percent of respondents saying they trust a healthcare-focused solution more.

The results demonstrate the industry’s increased focus and adoption of AI, while also highlighting the fact that healthcare still has a ways to go with implementation.

“The pandemic’s impact on financials and staff has heightened the need to invest in efficient and scalable processes, contributing to the burgeoning awareness and usage of AI and automation and moving it from a value-added option to a must-have capability,” the report concluded.

“However, automation has yet to move beyond the pilot stage for most healthcare organizations today, and some are stumbling as they launch projects or expand to other areas. The risk of failure makes selecting the right AI and automation partner all the more critical. Executives increasingly value partners that specialize in healthcare, can achieve ROI, and can serve multiple areas throughout the enterprise as they expand.”

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