Mayo Clinic and health imaging company Visage Imaging signed a collaboration agreement to research and develop artificial intelligence in healthcare.

Mayo Clinic signed a multi-year collaboration agreement with Visage Imaging, the US subsidiary of Australian company Pro Medicus Limited, to research and develop artificial intelligence in healthcare, according to a recent announcement.

The partnership will enable both parties to commercialize and make developments in artificial intelligence. Specifically, Mayo Clinic will leverage the Visage AI Accelerator, “an end-to-end AI solution that bridges research and diagnostic imaging on the same, unified platform,” Visage Imaging’s website states.

“Our AI Accelerator program was designed to closely align Visage’s engineering and product development capability with clinical research partners such as Mayo Clinic who have a depth of clinical knowledge and extensive research expertise,” said Malte Westerhoff, PhD, Visage Imaging Global CTO, in the announcement.

“It provides a unique set of tools for data de-identification, collection, curation, analysis and ‘path-to-production’ in research projects bringing the efficiency and speed of Visage technology to research, resulting in a unified link between the two domains.”

The collaboration agreement extends a previous six-year contract between Mayo Clinic and Visage Imaging established in 2016 that enabled the implementation of Visage 7 technology across Mayo Clinic’s radiology departments.

“We see AI playing a significant role in healthcare particularly in our field of imaging IT,” continued Westerhoff in the announcement.

“We have optimized our Visage 7 platform for AI enabling both our own, as well as third-party algorithms to be seamlessly integrated into the clinician’s desktop. We see this research collaboration agreement with Mayo Clinic as another significant piece of our AI strategy, one that has the potential to develop innovative AI solutions that meet well defined clinical goals and ultimately lead to better patient outcomes.”

In other artificial intelligence news, the University of Pittsburgh Schools of the Health Sciences (UPMC) recently launched a new company, Realyze Intelligence. The company will use both artificial intelligence and natural language processing to determine optimal treatments for patients with chronic diseases.

In addition, Ohio State University recently announced that it will be the first academic medical center in the US to use an FDA-approved tool for colonoscopy procedures, driven by artificial intelligence. The tool can detect polyps and lesions better than the human eye, aiding gastroenterologists in detecting colorectal cancer.

Google recently announced a new artificial intelligence-driven dermatology tool that allows people to use their phone’s camera to identify various dermatologic conditions.

These partnerships and innovations signify the growing popularity and trust in artificial intelligence and its applications in healthcare. But developments have a long way to go. Recent research suggests that developers will have to eliminate bias in artificial intelligence tools. Because the bulk of available patient data is from White males, algorithms may be inequitable and neglect to represent minorities. Feeding the programs well-rounded datasets is a way to combat this issue, but most public datasets do not currently reflect diverse populations.

Although these hurdles are not to be overlooked, artificial intelligence has proven to be a helpful assistant to providers in many cases. With the ability to analyze large amounts of data, predict the likelihood of illnesses, and even boost patient satisfaction, artificial intelligence is likely to become an asset in the future of healthcare.

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Domino’s is using AI ModelOps provider, Datatron, and its platform to improve the pizza company’s AI and machine learning capabilities, according to a press release.

The platform will allow Domino’s to automate and standardize the function of its AI models with a goal of improving in-store operations, finding untapped revenue opportunities and enhancing the customer experience.

“Machine learning models can provide significant value to an organization in several business applications, but without a solid ML operations pipeline, that value cannot be truly realized,” Zack Fragoso, Domino’s manager, data science and AI, said in the release.

“We use Datatron as our enterprise MLOps and governance platform for mission-critical projects.”

Datatron said Domino’s leadership was eager to have the ability to monitor models in real-time and understand how predictions were changing over time. Domino’s wanted to be able to refresh their models with new data as situational and operational truths changed over time. They also wanted to minimize the time required by their data science resources as new models were being rolled out, according to the release.

With the platform Domino’s can monitor and update models and create a birds-eye, multi-level view of key metrics to monitor how their models perform in production.

The Ann Arbor, Michigan-based pizza empire has used the product to:

• Improve labor scheduling by forecasting the in-store labor required to meet service goals.
• Streamline vehicle routing by creating efficient routes for drivers.
• Refine identifying the locations for building new stores.

“Technologies like ML [machine learning] and deep learning are becoming critically important for organizations looking to increase revenue and their competitive advantage. However, models must be carefully managed and appropriately governed to deliver their true value,” Datatron CEO Harish Doddi said in the release. “We are thrilled to assist Domino’s with their growth and to help the world leader in pizza delivery operationalize and govern their AI/ML models to achieve strategic business objectives, all without burdening their engineering and data science teams.”

Datatron is based in San Francisco. Domino’s has more than 17,200 stores worldwide.

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RepRisk, a leading ESG data science firm combining machine learning and human intelligence, and Crux Informatics (“Crux”), a cloud-based data delivery and operations platform, have entered into a strategic partnership to deliver RepRisk data across the financial services industry.

The partnership will enable financial institutions access to RepRisk data on ESG and business conduct risks on demand via a single API. As a result, financial institutions can focus on extracting meaningful ESG data from RepRisk for agile investment decisions without the added pressure of complicated technical integrations and implementation.

“We are excited to embark on this innovative partnership with Crux and that RepRisk is among the first ESG providers,” said Alexandra Mihailescu Cichon, Executive Vice President Sales and Marketing at RepRisk. “Investors and other financial industry professionals need reliable and daily-updated information on a company’s ESG and business conduct risks to make more informed investment decisions. In a data-driven world, this partnership will enable us to seamlessly deliver RepRisk’s ESG data – the largest dataset of ESG risks with a time series from 2007 – via external API and meet the need of our clients to be able to focus on data rather than onboarding and operating efforts.”

“We are thrilled to have RepRisk’s leading dataset on the Crux platform,” said Michael Rude, Head of Go-to-Market at Crux. “RepRisk fundamentally understands the challenges clients deal with in ingesting and making use of valuable data, and we are pleased to be working with them to remove the friction associated with delivering to their clients. We have seen a rise in interest in ESG data products and are happy to work with RepRisk to assist with the delivery of their data to a growing number of clients.”

RepRisk offers quantitative risk analytics and proprietary metrics for more than 140,000 public and private companies, from every sector and market across the globe, which serve leading financial institutions and corporates in their due diligence and risk management processes across their operations, business relationships, and investments.

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BlackRock and Microsoft Corp. have formed a strategic partnership to host BlackRock’s Aladdin infrastructure on the Microsoft Azure cloud platform.

The partnership brings enhanced capabilities to BlackRock and its Aladdin clients, which include many of the world’s most sophisticated institutional investors and wealth managers.

By adopting Microsoft Azure, BlackRock will both accelerate innovation on Aladdin through greater computing scale and unlock new capabilities to enhance the client experience. BlackRock will also leverage Microsoft Azure’s network of global data centers and capabilities to meet the localized needs of Aladdin clients, all while maintaining Aladdin’s highest standards for resiliency and security.

“As both a user and a provider of Aladdin, this decision reflects BlackRock’s ongoing commitment to continuous innovation and scalable operating solutions,” said Rob Goldstein, chief operating officer of BlackRock. “Aladdin infrastructure deployed on Microsoft Azure’s cloud platform will provide BlackRock with enhanced capabilities to deliver the best outcomes for our Aladdin clients.”

“By bringing Aladdin to the cloud, Microsoft will support BlackRock in further enhancing its client experience while also enabling continuous innovation in the financial services industry,” said Judson Althoff, executive vice president of Microsoft’s Worldwide Commercial Business. “Together, we will empower an ecosystem of financial services customers running their most critical workloads in the cloud.”

As the financial services industry looks to navigate ever-changing markets, institutions need integrated and scalable platforms to adapt to the growing complexity of managing data, risk management and advanced analytics to deliver innovative solutions to clients. To help support this trend, over time, the Microsoft Azure platform will enable BlackRock to accelerate innovation and collaboration between Aladdin and providers across the financial services ecosystem.

BlackRock and Microsoft will also work together on initiatives that leverage technology to improve and expand sustainability data and analytics.  The lack of standardized, high-quality data remains a significant hurdle in understanding the impact of sustainability-related risk on investment portfolios and company performance. Big data, machine learning and AI can all play a critical role in improving access to and the impact and quality of sustainability data.

The two firms will invite collaboration – whether from academics, startups, non-profits or others – on sustainability-related data, analytics and technology. As a first step, the firms will collaborate on challenge grants for organizations that use data and technology to understand and drive sustainability.

The firms will also provide technical expertise, leveraging Microsoft’s scale in computing, big data and AI, and BlackRock’s leading investment and portfolio management solutions to support a better understanding of corporate sustainability behaviour.

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There is a £2 million opportunity for new health data science partnership and projects to improve patient care as organisations across the UK are invited to contribute to a national programme that aims to enable better patient care through responsible use of health data used in health and care decisions.

Health Data Research UK – the national institute for health data science – is launching the opportunity that aims to help patients across the UK to benefit from health and care decisions that are informed by analysing large scale data. This work includes up to four projects and a brand-new partnership that will integrate with Health Data Research UK’s existing research activities.

Health Data Research UK is seeking a Better Care Partnership to lead a new data science initiative, which could receive up to £1.2 million. Initially funded for a period of three years, the Better Care Partnership will use continuous improvement methods to integrate clinical practice, large scale health data and advanced analytics to deliver insights for improving care for patients across the UK.

In addition, Health Data Research UK will also be supporting one year Catalyst Projects to demonstrate examples of how patient care can be improved through data-driven health and care decisions. Health Data Research UK is teaming up with the Health Foundation to jointly support these 12-month projects, which could each receive up to £200,000.

Organisations putting forward new partnership and project opportunities will be expected to demonstrate how they plan to listen to patients and understand their wishes about how their health data will be used. They will also be expected to show how patients will be involved at all stages of the project or partnership. The aim is to use health data responsibly and ethically with a clear focus on improving patient care.

Professor Simon Ball, Medical Director at University Hospitals Birmingham NHS Foundation Trust, and National Lead for Health Data Research UK’s Better Care priority, said: “As healthcare professionals we make hundreds of decisions a week with our patients. In doing so we aim to decide what will work best for each individual. Electronic healthcare records offer the opportunity to combine patients’ data with information on best practice, so that we can reliably deliver high quality care in complex settings and pressured environments. Beyond that we can use the resulting data on patients’ outcomes and experience, to continuously learn from, and improve on, everyday practice in ways that are applicable across the NHS.”

Every day doctors, nurses and patients in GP practices and hospitals across the UK are making countless decisions that impact on people’s health and care. These decisions are primarily based on the knowledge of the individual clinician and patient, relevant medical research and the data they can access. The UK has vast and rich data about people’s health and care, however this is often not available quickly for clinicians or patients to access to support their decision making. This causes delays and, in some cases, prevents the data from being analysed to deliver better care and improve people’s health. Both the Catalyst Projects and the Better Care Partnership, which will start in May 2020, aim to help address some of these issues.

The closing date for applying for the Catalyst and Better Care Partnership is 11 Mar 2020 at 4pm.

The Health Data Research UK’s website has more information about the Better Care Programme and details of this opportunity.

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Dotscience, a provider of DevOps for Machine Learning (MLOps) solutions, is forming partnerships with GitLab and Grafana Labs, along with strengthening integrations with several platforms and cloud providers.  

The company is deepening integrations to include Scikit-learn, H2O.ai and TensorFlow; expanding multi-cloud support with Amazon Web Services (AWS) and Microsoft Azure; and a entering a joint collaboration with global enterprises to develop an industry benchmark for helping enterprises get maximum ROI out of their AI initiatives.

“MLOps is poised to dominate the enterprise AI conversation in 2020, as it will directly address the challenges enterprises face when looking to create business value with AI,” said Luke Marsden, CEO and founder at Dotscience. “Through new partnerships, expanded multi-cloud support, and collaborations with MLOps pioneers at global organizations in the Fortune 500, we are setting the bar for MLOps best practices for building production ML pipelines today.”

Grafana Labs, the open observability platform, and Dotscience are partnering to deliver observability for ML in production.

With Dotscience, ML teams can statistically monitor the behavior of ML models in production on unlabelled production data by analyzing the statistical distribution of predictions.

The partnership simplifies the deployment of ML models to Kubernetes and adds the ability to set up monitoring dashboards for deployed ML models using cloud-native tools including Grafana and Prometheus, which reduces the time spent on these tasks from weeks to seconds.

As a GitLab Technology Partner, Dotscience is extending the use of its platform for collaborative, end-to-end ML data and model management to the more than 100,000 organizations and developers actively using GitLab as their DevOps platform.

Dotscience is now available on the AWS Marketplace, enabling AWS customers to easily and quickly deploy Dotscience directly through AWS Marketplace’s 1-Click Deployment, and through Microsoft Azure.

Dotscience has expanded the frameworks in which data scientists can deploy tested and trained ML models into production and statistically monitor the productionized models, to include Scikit-learn, H2O.ai and TensorFlow.

These new integrations make Dotscience’s recently added deploy and monitor platform advancements—the easiest way to deploy and monitor ML models on Kubernetes clusters—available to data scientists using a greater range of ML frameworks.

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