Computer scientists could only dream of the capabilities that an average consumer might now take for granted at the time that the field of AI (artificial intelligence) was founded more than 50 years ago.

Microsoft and partners combine the cloud, AI, research and industry expertise to focus on transforming health care

By Peter Lee as written on blogs.microsoft.com

The goal is noble: Empower people to lead healthier lives. And yet, few industries in the world face more complex problems than health care. Disparate and disconnected information systems, the uncertainties within regulatory environments around the world and the inevitable disruptions in core business models all pose perplexing and interlocking challenges.

As we look at some of the challenges in health care, a natural question we ask ourselves is, How can Microsoft bring its capabilities to bear to solve some of these problems?

It’s a big challenge. But we believe technology – specifically the cloud, AI and collaboration and business optimization tools – will be central to health care transformation.

Making a difference in health care will require all that Microsoft can bring, fused with the industry expertise and experience from our partners: leading health care organizations and the companies that serve them.

We are incredibly energized about the opportunities to make a difference in health care. We’ve been listening carefully to our customers and partners within the health care sector, and we’ve heard their message: Let’s work together, innovate together and create solutions that can empower people to lead healthier lives.

Today, we are expanding our commitment to building a healthier future with new initiatives and solutions, making it easier for health industry partners and organizations to use intelligent technology to improve the lives of people around the world.

Healthcare NExT: Fusing research, AI and industry expertise through partners

Healthcare NExT, a new initiative to dramatically transform health care, will deeply integrate greenfield research and health technology product development, as well as establish a new model at Microsoft for strategic health industry partnerships. Through these collaborations between health care partners and Microsoft’s AI and Research organization, our goal is to enable a new wave of innovation and impact using Microsoft’s deep AI expertise and global-scale cloud.

This initiative includes investments in resources for our partners to capture new opportunities to apply AI to healthcare, such as the Microsoft AI in Health Partner Alliance, an expanding group of partners focused on advancing health technology. Alliance members will receive unique training and access to Microsoft technologies, engineering expertise and data sets.

Transforming patient and clinician empowerment with UPMC

The first planned strategic research partnership for Microsoft’s Healthcare NExT initiative is with UPMC (University of Pittsburgh Medical Center), one of the largest integrated health care delivery networks in the United States. The $13 billion Pittsburgh-based system, comprising more than 25 hospitals, a 3 million-member health plan and 3,600 physicians, will be a core partner in our efforts to improve health care delivery through a series of projects, beginning with a focus on transforming clinician empowerment and productivity. With UPMC’s long track record of clinical and commercial innovation and Microsoft’s expertise in advanced AI capabilities, the two organizations plan to work together to bring innovative new solutions to market, beginning with implementation at UPMC.

“Despite UPMC’s efforts to stay on the leading edge of technology, too often our clinicians and patients feel as though they’re serving the technology rather than the other way around. With Microsoft, we have a shared vision of empowering clinicians by reducing the burden of electronic paperwork and allowing the doctor to focus on the sacred doctor-patient relationship,” said Steven D. Shapiro, M.D., chief medical and scientific officer of UMPC and president of UPMC’s Health Services division.

Additional collaborations from Healthcare NExT include partners applying the cloud, AI and research to some of the biggest problems in health care:

• HealthVault Insights is a new research-based project designed to allow partners to generate new insights about patient health, drive adherence to care plans and encourage patient engagement powered by the latest scientific advances in machine learning. Tribridge and System C & Graphnet Care Alliance are building on HealthVault Insights to create innovative solutions for patient adherence to provider care plans.

• Microsoft Genomics is making the sample-to-answer process fast and easy through an Azure-powered genome analysis pipeline and an orchestrated ecosystem of innovative partners including BC Platforms and DNAnexus.

• Microsoft’s AI health chatbot technology is also a research-based project that will enable partners to build AI-powered conversational health care tools. MDLIVE intends to use our health bot technology to help patients self-triage inquiries before they interact with a doctor via video. Premera Blue Cross, the largest health plan in the Pacific Northwest, plans to use our health bot technology to transform how members can look up information about their health benefits. Health Navigator’s symptom checker brings best practices to other customers and partners.

• Project InnerEye is a research-based, AI-powered software tool for radiotherapy planning. The goal of the project is to allow dosimetrists and radiation oncologists to achieve 3D contouring of patients’ planning scans in minutes rather than hours. The assistive AI technology gives experts full control of the output accuracy while enjoying high levels of consistency and potential cost savings.

Enabling 21^st-century house calls powered by the Microsoft cloud

Microsoft Office 365 Virtual Health Templates provide new functionality to connect people and providers through voice, video and messaging in any interface or application, powered by Skype for Business. The open source templates make it easy for industry partners, developers and enterprises to build solutions to provide care wherever patients may be.

RingMD, Careflow, Cambio and GE Healthcare have built from Office 365 Virtual Health Templates compelling and easy to use experiences.

Addressing health care business optimization with SaaS apps

New services from our partner ecosystem, powered by the Microsoft cloud, help address business process challenges outside of the clinic. Available today is CGI ProperPay for claims analytics. ProperPay provides predictive analytics, rules management and best practices for reducing health care claims fraud, waste and abuse, a $450 billion-plus problem driving up health care costs around the globe. CGI ProperPay for claims analytics joins a growing number of business and engagement applications in the Microsoft AppSource catalog like Tribridge’s Health360 Care Coordination.

Looking to the future

With any significant advance in technology it’s important to consider the unintended consequences, as well as the benefits. At Microsoft, we’re grounding our efforts in a set of core design principles that focus on the human benefit of AI, transparency and accountability. We believe that ethics and design go hand in hand.

Further, we understand that security, privacy, and compliance remain a top priority for health organizations. Microsoft Chief Information Security Officer for Health Hector Rodriguez recently reinforced our commitment to customers highlighting key investments across these core principles of trust in technology.

At the intersection of health, technology and people lies great promise. Our mission is to empower every person and organization to achieve more, and we’re excited to meet many of you next week at HIMSS17 and continue our close partnership in health care to achieve more together. If you’re at HIMSS17 next week in Orlando, Florida, be sure to stop by our booth No. 2509 to see our solutions in action. Follow our HIMSS17 story on @Health_IT to learn more.

Conversations on AI

As written on news.microsoft.com

Microsoft has been investing in the promise of artificial intelligence for more than 25 years — and this vision is coming to life with new chatbot Zo, Cortana Devices SDK and Skills Kit, and expansion of intelligence tools.

“Across several industry benchmarks, our computer vision algorithms have surpassed others in the industry — even humans,” said Harry Shum, executive vice president of Microsoft’s Artificial Intelligence (AI) and Research group, at a small gathering on AI in San Francisco on Dec. 13.
“But what’s more exciting to me is that our vision progress is showing up in our products like HoloLens and with customers like Uber building apps to use these capabilities.”

When Bill Gates created Microsoft Research in 1991, he had a vision that computers would one day see, hear and understand human beings — and this notion attracted some of the best and brightest minds to the company’s labs.

Last month, Microsoft became the first in the industry to reach parity with humans in speech recognition. There’s also been groundbreaking work with Skype Translator — now available in 9 languages — an example of accelerating the pipeline from research to product. With Skype Translator Microsoft has enabled people to understand each other, in real time, while talking to others in all corners of the world. But what about the dream of face-to-face, real-time translation?

Using this new intelligent language and speech recognition capability, Microsoft Translator can now simultaneously translate between groups speaking multiple languages in-person, in real-time, connecting people and overcoming barriers.

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Microsoft Connected Vehicle Platform Helps Automakers Transform Cars

By Peggy Johnson as written on blogs.microsoft.com

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Historic milestone: Microsoft researchers achieve human parity in conversational speech recognition

By Athima Chansanchai as written on blogs.microsoft.com

Microsoft has made a major breakthrough in speech recognition, creating a technology that understands a conversation as well as a person does.

In a paper published Monday, a team of researchers and engineers in Microsoft Artificial Intelligence and Research reported a speech recognition system that makes the same or fewer errors than professional transcriptionists.  The researchers reported a word  error rate (WER) of 5.9 percent, down from the 6.3 percent WER the team reported just last month.

The 5.9 percent error rate is about equal to that of people who were asked to transcribe the same conversation, and it’s the lowest ever recorded against the industry standard Switchboard speech recognition task.

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How web search data might help diagnose serious illness earlier

By Mike Brunker as written on blogs.microsoft.com

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Decades of computer vision research, one ‘Swiss Army knife’

By Allison Linn as written on blogs.microsoft.com

When Anne Taylor walks into a room, she wants to know the same things that any person would.

Where is there an empty seat? Who is walking up to me, and is that person smiling or frowning? What does that sign say?

For Taylor, who is blind, there aren’t always easy ways to get this information. Perhaps another person can direct her to her seat, describe her surroundings or make an introduction.

There are apps and tools available to help visually impaired people, she said, but they often only serve one limited function and they aren’t always easy to use. It’s also possible to ask other people for help, but most people prefer to navigate the world as independently as possible.

That’s why, when Taylor arrived at Microsoft about a year ago, she immediately got interested in working with a group of researchers and engineers on a project that she affectionately calls a potential “Swiss Army knife” of tools for visually impaired people.

“I said, ‘Let’s do something that really matters to the blind community,’” said Taylor, a senior project manager who works on ways to make Microsoft products more accessible. “Let’s find a solution for a scenario that really matters.”

That project is Seeing AI, a research project that uses computer vision and natural language processing to describe a person’s surroundings, read text, answer questions and even identify emotions on people’s faces. Seeing AI, which can be used as a cell phone app or via smart glasses from Pivothead, made its public debut at the company’s Build conference this week. It does not currently have a release date.

Taylor said Seeing AI provides another layer of information for people who also are using mobility aids such as white canes and guide dogs.

“This app will help level the playing field,” Taylor said.

At the same conference, Microsoft also unveiled CaptionBot, a demonstration site that can take any image and provide a detailed description of it.

Very deep neural networks, natural language processing and more

Seeing AI and CaptionBot represent the latest advances in this type of technology, but they are built on decades of cutting-edge research in fields including computer vision, image recognition, natural language processing and machine learning.

In recent years, a spate of breakthroughs has allowed computer vision researchers to do things they might not have thought possible even a few years before.

“Some people would describe it as a miracle,” said Xiaodong He, a senior Microsoft researcher who is leading the image captioning effort that is part of Microsoft Cognitive Services. “The intelligence we can say we have developed today is so much better than six years ago.”

The field is moving so fast that it’s substantially better than even six months ago, he said. For example, Kenneth Tran, a senior research engineer on his team who is leading the development effort, recently figured out a way to make the image captioning system more than 20 times faster, allowing people who use tools like Seeing AI to get the information they need much more quickly.

A major a-ha moment came a few years ago, when researchers hit on the idea of using deep neural networks, which roughly mimic the biological processes of the human brain, for machine learning.

Machine learning is the general term for a process in which systems get better at doing something as they are given more training data about that task. For example, if a computer scientist wants to build an app that helps bicyclists recognize when cars are coming up behind them, it would feed the computer tons of pictures of cars, so the app learned to recognize the difference between a car and, say, a sign or a tree.

Computer scientists had used neural networks before, but not in this way, and the new approach resulted in big leaps in computer vision accuracy.

Several months ago, Microsoft researchers Jian Sun and Kaiming He made another big leap when they unveiled a new system that uses very deep neural networks – called residual neural networks – to correctly identify photos. The new approach to recognizing images resulted in huge improvements in accuracy. The researchers shocked the academic community and won two major contests, the ImageNet and Microsoft Common Objects in Context challenges.

Tools to recognize and accurately describe images

That approach is now being used by Microsoft researchers who are working on ways to not just recognize images but also write captions about them. This research, which combines image recognition with natural language processing, can help people who are visually impaired get an accurate description of an image. It also has applications for people who need information about an image but can’t look at it, such as when they are driving.

The image captioning work also has received accolades for its accuracy as compared to other research projects, and it is the basis for the capabilities in Seeing AI and Caption Bot. Now, the researchers are working on expanding the training set so it can give users a deeper sense of the world around them.

Margaret Mitchell, a Microsoft researcher who specializes in natural language processing and has been one of the industry’s leading researchers on image captioning, said she and her colleagues also are looking at ways a computer can describe an image in a more human way.

For example, while a computer might accurately describe a scene as “a group of people that are sitting next to each other,” a person may say that it’s “a group of people having a good time.” The challenge is to help the technology understand what a person would think was most important, and worth saying, about the picture.

“There’s a separation between what’s in an image and what we say about the image,” said Mitchell, who also is one of the leads on the Seeing AI project.

Other Microsoft researchers are developing ways that the latest image recognition tools can provide more thorough explanations of pictures. For example, instead of just describing an image as “a man and a woman sitting next to each other,” it would be more helpful for the technology to say, “Barack Obama and Hillary Clinton are posing for a picture.”

That’s where Lei Zhang comes in.

When you search the Internet for an image today, chances are high that the search engine is relying on text associated with that image to return a picture of Kim Kardashian or Taylor Swift.

Zhang, a senior researcher at Microsoft, is working with researchers including Yandong Guo on a system that uses machine learning to identify celebrities, politicians and public figures based on the elements of the image rather than the text associated with it.

Zhang’s research will be included in the latest vision tools that are part of Microsoft Cognitive Services. That’s a set of tools that is based on Microsoft’s cutting-edge machine learning research, and which developers can use to build apps and services that do things like recognize faces, identify emotions and distinguish various voices. Those tools also have provided the technical basis for Microsoft showcase apps and demonstration websites such as how-old.net, which guesses a person’s age, and Fetch, which can identify a dog’s breed.

Microsoft Cognitive Services is an example of what is becoming a more common phenomenon – the lightning-fast transfer of the latest research advances into products that people can actually use. The engineers who work on Microsoft Cognitive Services say their job is a bit like solving a puzzle, and the pieces are the latest research.

“All these pieces come together and we need to figure out, how do we present those to an end user?” said Chris Buehler, a software engineering manager who works on Microsoft Cognitive Services.

From research project to helpful product

Seeing AI, the research project that could eventually help visually impaired people, is another example of how fast research can become a really helpful tool. It was conceived at last year’s //oneweek Hackathon, an event in which Microsoft employees from across the company work together to try to make a crazy idea become a reality.

The group that built Seeing AI included researchers and engineers from all over the world who were attracted to the project because of the technological challenges and, in many cases, also because they had a personal reason for wanting to help visually impaired people operate more independently.

“We basically had this super team of different people from different backgrounds, working to come up with what was needed,” said Anirudh Koul, who has been a lead on the Seeing AI project since its inception and became interested in it because his grandfather is losing his ability to see.

For Taylor, who joined Microsoft to represent the needs of blind people, it was a great experience that also resulted in a potential product that could make a real difference in people’s lives.

“We were able to come up with this one Swiss Army knife that is so valuable,” she said.

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Aiming to Deliver New Drugs Faster at Less Cost in the Cloud

Researchers from Molplex, a small drug discovery company; Newcastle University; and Microsoft Research Connections are working together to help scientists around the world deliver new medicines more quickly and at lower cost. This partnership has helped Molplex develop Clouds Against Disease, an offering of high-quality drug discovery services based on a new molecular discovery platform that draws its power from cloud computing with Windows Azure.

Rethinking Drug Discovery
David Leahy, co-founder and chief executive officer of Molplex, envisions a way to help pharmaceutical researchers anywhere in the world form effective drug discovery teams without large investments in technology or fixed running costs. "It takes massive computing resources to search through chemical and biological databases looking for new drug candidates. Our Clouds Against Disease solution dramatically reduces the time and cost of doing that by providing computation and chemical analysis services on demand," Leahy says.

Molplex regards drug discovery as a big data and search optimization problem. Clouds Against Disease uses its computational molecular discovery platform to automate decision making that is traditionally the scientists’ task.

"Instead of having teams of scientists scanning chemical information, our software searches for structures that have multiple properties matching the search criteria," explains Leahy. "When we integrate that with highly automated chemical synthesis and screening, it becomes a much more efficient and productive way of doing drug discovery."

Data Manipulation on a Larger Scale
In a recent pre-clinical study, the company applied its computational platform to more than 10,000 chemical structure and biological activity data sets. This action generated 750,000 predictive relationships between chemical structure and biological effect. After generating numerous possible outcomes, Molplex then used the same validation criteria that scientists would use to narrow down the 750,000 relationships to just 23,000 models covering 1,000 biological and physico-chemical properties, a relatively small data set that humans could then manage. "It would have taken hundreds of scientists several years to do this the conventional way," Leahy

Windows Azure was critical to the success of Clouds Against Disease. Molplex can access 100 or more Windows Azure nodes—in effect, virtual servers—to process data rapidly. The physical-world alternative would be to source, purchase, provision, and then manage 100 physical servers, which represents a significant investment in up-front costs. Before they could begin drug research, scientists taking this traditional approach would have to raise millions of dollars, but Windows Azure helps eliminate start-up costs by allowing new companies to pay for only what they use in computing resources.

Vladimir J. Sykora, co-founder and chief operating officer for Molplex, explains that the Molplex computational platform runs algorithms his company developed to calculate the numerical properties of molecules rapidly. Consequently, Molplex has been able to produce drug discovery results on a much larger scale than what was previously feasible. "We would not have been able to predict so many compounds without the cloud computing resources enabled by Windows Azure," asserts Sykora. "The speed and high level of detail provided by Windows Azure allow us to explore far beyond what would have been possible with traditional hardware resources."

Fighting Tropical Diseases
Molplex is embarking on a new collaboration with the Malaysian government to search for drugs that fight tropical diseases. This search has always been a lower priority for drug companies because the market is smaller, making it a less desirable commercial prospect. The traditional drug discovery program is geared to $1 billion a year blockbuster drugs; however, there are fewer opportunities today for drugs with that level of commercial potential.

Increasingly, scientists are researching tropical diseases that affect smaller populations; radically reducing the cost of drug discovery makes it feasible for scientists to tackle them. "Unlocking drug discovery technology from a physical location with the cloud has tremendous potential to help researchers work on curing these diseases faster and at less cost," asserts Leahy, "wherever they are in the world."

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