AI in medicine is one of the most fascinating frontiers because its applications directly affect patient outcomes. The computational health data scientists at UCSF are among the leaders shaping how artificial intelligence is responsibly developed and applied in real-world care – where innovation meets impact. Dr. Atul Butte, who tragically passed away last summer after a long battle with cancer, mentored this team. They gathered on October 31, 2025 in Star Trek-themed Halloween costumes to share reflections on his impact on their work, while providing exciting updates, during the monthly UCSF AI Seminar Series. This heartfelt event was hosted by the Bakar Computational Health Sciences Institute (BCHSI), UCSF Division of Clinical Informatics and Digital Transformation (DoC-IT), UC Berkeley – UCSF Computational Precision Health Program, and UCSF Department of Epidemiology and Biostatistics.

Key Takeaways

1. Start with the question — meaningful AI begins with the problem, not the tool.

2. Validate with a clinical simulation — models must prove their value before implementation.

3. Navigate thoughtfully — success requires diligence, awareness, and collaboration to avoid misinformed or premature applications of AI.

A Celebration of Vision, Collaboration, and Impact

The October UCSF AI Seminar brought together faculty, clinicians, and data scientists to honor the legacy of Dr. Atul Butte, whose pioneering work defined UCSF’s modern approach to data-driven medicine.

Held on Halloween, the event blended reflection and good humor: attendees came dressed in Star Wars and other costumes, while a photo of Atul—remembered fondly as a Star Trek fan—set a warm, personal tone.

The seminar showcased the extraordinary progress being made in applying AI to two of medicine’s greatest challenges: Alzheimer’s disease and cancer. Featured speakers Marina Sirota, PhD, and Julian Hong, MD, MS—both protégés of Dr. Butte—shared how UCSF continues to build on his vision, bridging computation, collaboration, and clinical impact.

“You could fill a couple of hours talking about the problems of AI in medicine,” one participant noted, “but the key is to do the best work possible and think systematically about every step.” 

The seminar audience quickly learned that this is the team to follow when it comes to launching AI innovations in medicine, balancing both first-of-their-kind technologies with what is most efficient, effective, safe and trustworthy for clinicians and patients alike.

Using AI to Tackle Alzheimer’s Disease

Marina Sirota, PhD, opened the seminar with “From Data to Knowledge: Integrating Clinical and Molecular Data for Predictive Medicine.”

She discussed how AI and molecular data can be used to better understand and treat Alzheimer’s disease (AD)—a condition that remains difficult to diagnose early and challenging to treat effectively.

Her research combines computational biology, AI, and large-scale molecular data to uncover new treatment targets and accelerate precision medicine approaches. By integrating real-world clinical data and knowledge networks, her team is helping bridge the gap between discovery and care.

Marina reflected that Dr. Butte’s mentorship taught her to always start with a well-formed question—not with the methods or tools. Sometimes, she observed, “the solution is simple and doesn’t necessarily require data science.”

Applying AI to Help Cancer Patients and Advance Care

Julian Hong, MD, MS, followed with “The Future of Evidence-Based Medicine is Data-Driven Medicine: Leveraging Data and AI in the Cancer Clinic.”

He described how his team uses real-world data and AI tools to improve cancer care, work that became especially urgent during and after the COVID-19 pandemic.

Julian’s research builds on Dr. Butte’s vision of data-driven medicine—applying AI-guided strategies to reduce treatment-related toxicities and improve patient outcomes. His team leverages UCSF’s Information Commons, Wynton, and clinical NLP tools to create actionable predictive models that directly inform care.

He also shared updates from Weill Cancer Hub West, which connects research insights with clinical decision-making—demonstrating how AI can move from theory to impact.

AI in Medicine: Promise, Challenges, and Actionability

The discussion underscored both the promise and the complexity of using AI responsibly in healthcare. Speakers acknowledged the challenge of actionability—ensuring that AI-generated insights are not only predictive but useful for patients and clinicians.

For example, if a model predicts a high risk of Alzheimer’s disease, what can be done with that information? The next steps might include enrolling in a clinical trial or pursuing non-therapeutic interventions, underscoring that AI’s value depends on connecting data to decisions.

Both Marina and Julian emphasized the need for researchers to be aware of potential pitfalls in implementing AI in medicine. Their shared message: the path to success requires a systematic, thoughtful, and collaborative approach. These speakers and other members of the team, many of whom were in the audience, shared a profound understanding of their craft, demonstrating the criticality of their expertise in both technical innovation a deep understanding and consideration of the long-term impact on people and society.

Validation: The Core of Responsible Innovation

Sharat Israni, Executive Director of BCHSI, highlighted validation as one of Dr. Butte’s defining principles.

Atul was an early adopter of new technologies, but he always insisted on rigorous validation, especially in clinical settings. This insistence on testing and proving models before implementation continues to distinguish AI in medicine from other applications of AI—ensuring that innovation remains both ethical and impactful.

“Atul was in the early adoption of new technologies coming out of research, but he insisted you validate early as well. This was a holy thing. If you see it coming out, validate it up front.”

Continuing the Mission

Throughout the seminar, speakers reflected on Atul’s enduring influence—his curiosity, rigor, and focus on questions that matter.

They agreed that while many in this field are researchers rather than clinicians, their shared goal remains to make their work useful for the patient.

We are at a pivotal moment in the history of medicine, as revolutions in biology and immunology converge with advances in AI and data science. Dr. Butte called this a “revolution in health care.”

Thanks to the talented team Atul put in place, UCSF is poised to make measurable differences in the lives of patients and families facing Alzheimer’s disease, cancer, and many other complex conditions, thanks to combined advances in AI, data science and molecular biology.

Background reading

1. The UCSF AI Seminar Series is a monthly forum for anyone interested in the intersection of AI and healthcare. See past events and learn more here → UCSF AI Seminar Series
2. Learn more about UCSF BCHSI → UCSF Bakar Computational Health Sciences Institute website
3. Gift Launches $200M Initiative for the Weill Cancer Hub West , UCSF News, July 24, 2025. BCHSI affiliated faculty Julian Hong’s Project IMPACT is awarded to build artificial intelligence systems that integrate clinical and biological data for precise, personalized cancer treatments.

[Cover Photo: Attendees in Halloween costumes, with a tribute image of Dr. Atul Butte, a devoted Star Trek fan. From the left, Drs. Peter Washington, Angela Rizk-Jackson, Marina Sirota, Andrew Bishara, Julian Hong, Jean Feng]

Other photos featuring presenters and members of the BCHSI team can be found below.

“We have a binary view – either ‘for’ or ‘against’ – this is very damaging for society or any debate.”

This provocative comment helped set the stage for a fascinating conversation on both offline and online behaviors and tendencies that affect human rights on an international basis. 

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Last week, I had the opportunity to attend “From Brussels to the Bay: the EU and the UN’s efforts to reinforce democracy online.” They covered the critical intersection between the online world and human rights. This local, San Francisco-based discussion, with a strong global perspective, was hosted by the “father” of the EU Digital Services Act (DSA), Gerard de Graaf Senior EU Envoy for Digital to the U.S., as well as the Norwegian Consul, and included thought-leader panelists, ranging from the UN High Commissioner for Human Rights, Volker Türk to the UC Berkeley Chancellor’s Public Scholar, David Evan Harris, among other distinguished panelists and guests. Together, they generated a lively conversation which touched on the role of  dominant Silicon Valley companies (Google, Meta and others) influencing digital information exchange on global, and each of us, on the eve of the implementation of the Digital Services Act on Feb 17, 2024, two days after their event.

[In-person panelists, moderated by Alexis Wichowski (Professor of Professional Practice at Columbia University)(left), are listed below, and, from left to right are: Volker Türk (UN High Commissioner for Human Rights), Gerard de Graaf (Senior EU Envoy for Digital to the U.S.), Naomi Shiffman (Head of Data and Implementation at Meta Oversight Board) and David Evan Harris (UC Berkeley “Chancellor’s Public Scholar”)]

My takeaways from the discussion

1. Human rights norms exist for tech and social media. Private companies have operated  in relatively unregulated environments when it comes to these realms.
2. Upcoming elections in 70 countries this year must safeguard fundamental rights and promote civic discourse.
3. Human rights starts offline, with nearly 50% of countries being autocracies or with autocracy elements. Further, the way information flows, including hate speech, has been accelerated with online tools. Ideally, in both digital and off-line realms, dialogue and nuanced consideration of opposing views would be the norm vs a “black” or “white” view of politics. 
4. We need to demonstrate the value of democracies and ensure that democratic values guide corporate behavior. The panelists conclude that this requires regulation, such as what is happening in Europe.
5. Silicon Valley companies (Alphabet (Google) Amazon, Apple, Meta, Microsoft) represent a culture of rapid innovation, which has spawned rapid growth, but, at the same time clashes with public interest of safety and moderation. (There is a culture of “moving fast and breaking things.”) Many platform models optimize engagement, at the expense of providing people with the full range of information they need to make complex decisions based on nuanced information that also is confirmed to be factually correct. Human rights norms exist for tech and social media. Private companies have operated  in relatively unregulated environments when it comes to these realms.
6. The discussion of regulation started 5 years ago with the advent of social media and has been reinvigorated by the introduction of generative AI. AI’s impact, including deep fakes, requires better training and transparency in language models. There is massive concern of the destructive impact of AI on the 2024 elections.
7. Today, the EU’s regulatory framework is a part of many conversations regarding AI in the US. The Digital Services Act (DSA) enforcement, which began on February 17, 2024, emphasizes regulation without stifling free speech, often a concern among Americans.

Event Background

Hosted at the new EU Office for the west coast, located on Market Street in San Francisco, CA.

1. Event Hosts:
   1. Gerard de Graaf (Senior EU Envoy for Digital to the U.S.),  and Joanna Smolinska (Deputy Head of EU Office in SF)
   2.  Gry Rabe Henriksen (Consul General of Norway to SF), 
2. Event Panelists:
   1. Volker Türk (UN High Commissioner for Human Rights) 
   2. Prabhat Agarwal (Head of Unit DSA, European Commission, DG CNECT), 
   3. Naomi Shiffman (Head of Data and Implementation at Meta Oversight Board) 
   4.  David Evan Harris (Chancellor’s Public Scholar at UC Berkeley). 
   5. Tormod C. Endresen, the new Permanent Representative of the Republic of Norway to the United Nations Office at Geneva 
   6. Gerard de Graaf (Senior EU Envoy for Digital to the U.S.)
   7. The discussed was moderated by Alexis Wichowski (Professor of Professional Practice at Columbia University)
3. Audience members/guests
   1. The event attracted an international audience, fostering discussions on the intersection of technology, ethics, society, and economics, among other factors. 

[Online panelists (left) Tormod C. Endresen, the new Permanent Representative of the Republic of Norway to the United Nations Office at Geneva.]

[Online panelist (right) Prabhat Agarwal (Head of Unit DSA, European Commission, DG CNECT)]

Thanks to the collaboration between academic medical institutions like The University of Washington and data science startups, such as MDClone, a health care informatics company, synthetic data is advancing to the point that it may soon be a viable tool to allow institutions to share information about patients in ways that have never before been possible. 

This week, researchers from The University of Washington School of Medicine published two studies: in (1) the Journal of the American Medical Informatics Association (JAMIA);  and (2) the Journal of Medical Internet Research (JMIR). These studies demonstrated that analyzing synthetic data generated from real COVID-19 patients accurately replicates the results of the same analyses conducted on the real patient data.

Co-author of one of the papers, Philip R.O. Payne, PhD, Biomedical Informatician & Data Scientist, Janet & Bernard Becker Professor & Director of The University of Washington, and Associate Dean & Chief Data Scientist at Wash Med, describes it as a simulation. “We’re trying to build the hurricane-track equivalent for pandemics, using large amounts of data,” said Payne.

Using conventional methods of sharing de-identified patient records, institutions must de-identify the data, be certain that it cannot be re-identified, and ensure timely access to sufficient quantities of data to make it useful for large-scale studies. With the use of synthetic data, those problems are no longer an issue because the data is manufactured and contains no identifying elements that could be linked back to a person. Further, because it is not associated with individual health records, it can be more easily shared across institutions. 

What’s next?

The research reveals that data synthesis platforms are expected to help translate clinical data into faster COVID-19 insights and decrease barriers to data access by multiple stakeholders.

It will be fascinating to witness progress in a field that promises to address one of the largest bottlenecks in the development of diagnostic, therapeutic or preventative solutions – sufficient data that is easily accessed and shared.

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FAQ’s

What is synthetic data?

Synthetic data are generated based on actual data, but do not tie to EHRs or any other source of individual patient records. As a result, there is no risk of re-identifying patient data as there would be in using actual patient records. 

How is the data artificially generated?

Synthetic data is created by recreating the statistical characteristics of the real patients, such as measures of blood pressure, body mass index and kidney function. It creates a set of new records with human characteristics, but which do not tie back to any one individual’s PHI (name, address, birthday), but only a set of associated symptoms and other factors such as behaviors.

What are the applications of synthetic data ?

With leading-edge informatics techniques and tools, including pattern recognition and machine learning techniques, the data could predict, for example, which patients are at highest risk of needing intensive care or ventilators. It also could help identify patterns in treatment strategies to see if drugs that a patient is already taking for a different condition help or hinder their progress.

Sources:

“Synthetic data mimics real patient data, accurately models COVID-19 pandemic – National synthetic dataset boosts coronavirus research, helps prepare for future pandemics,” Washington University School of Medicine in St. Louis News Release, April 27, 2022

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: Results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C), Journal of the American Medical Informatics Association,  March 31, 2022

The National COVID Cohort Collaborative: Analyses of Original and Computationally Derived Electronic Health Record Data, Journal of Medical Internet Research, October 4, 2021

“Data scientists find communicating their work not only foreign but distracting.”

A critical snap shot from this remarkable HBR article: “The presentation of data science to lay audiences—the last mile—hasn’t evolved as rapidly or as fully as the science’s technical part. It must catch up.”

The answer lies is #communicator skills, as well as in the concept of #empathy, underscored throughout this piece. I define this as the art of ensuring that those with differing skillsets communicate with one another clearly. This will allow teams to construct the linguistic and conceptual bridges needed to help data science reach its true value among the organizations it serves, including any industry that isn’t “tech,” from health care to retail and almost any other.

From an HR perspective, the article also delves into the art of understanding skills vs roles and how to create the most effective teams with a skillset that goes beyond traditional functional. It makes great sense and will be essential for many of us to implement in our orgs to ultimately arrive at the main goal – filling in the perpetual gaps and extracting the true value of what data science has to offer us today.

For those tracking progress in the field of digital health, in general, and the aspect that covers data, AI and personalization of health care through data insights, an important piece was published this week in The MIT Technology Review, entitled “It took a pandemic, but the US finally has (some) centralized medical data.” It reveals important news in big data mining in the health care industry that happened during the COVID crisis, providing both a broad overview and specific examples that provide a clear description of the impact of COVID and data sharing on an industry formerly known for a lack of public sharing of large data sets. With greater access to large, consistent data sets, the piece paints a bright future for personalized health care and other public and/or behavioral health other issues that rely upon large, standardized data sets.

In 2020, I reviewed colleague definitions of “Digital Health” (in alpha order), as follows, below. 

Comparing Definitions

In terms of the broadest description, I enjoyed this one provided by Sharat Israni  Exec Dir & CTO, Bakar Computational Health Science Institute, UCSF. When I asked him how he defined digital health, he replied, “That which is not paper-based.” and went on to say that it is just about all aspects of health care. His comment is not far from the definition on the Startup Health website, What was once defined as “digital health” is converging across all health sectors – in other words: digital health = health. 

Between a paper-based system and “everything,” however, I believe that there lies a definition that will help us evaluate the new options, which is important in determining where we will, as an industry, invest our time, money and take a risk, as patients, in order to shape an industry that has a truly beneficial effect on society. I agree that there is a danger in combining two industries that have not, traditionally, spoken the same language, as Robert Wachter proclaims in his book Digital Doctor, and who has advocated for improved cross-pollination across these two sectors. I believe that the more all of us pay attention and ask ourselves about the quality of digital health solutions, the more we can focus on the ones that will leave a long-lasting impact.

Colleague Definitions:

1. HIMSS defines digital health, March 2020:  HIMSS is releasing a new definition of digital health to serve as a benchmark for the global health community: Digital health connects and empowers people and populations to manage health and wellness, augmented by accessible and supportive provider teams working within flexible, integrated, interoperable and digitally-enabled care environments that strategically leverage digital tools, technologies and services to transform care delivery.
2. JP Morgan 2020/CNBC Article Jan 2020: “Some attendees felt the lack of a clear definition for “digital health” might be hurting the sector. Digital health is broadly considered the intersection of health and technology, but the term is so overused and over-hyped, it’s no longer clear what it means.”
3. MD-Disrupt: Healthtech is defined as the application of technology to solve problems in healthcare—think wearables, apps, cellphones, connected devices,  software, databases, etc.  It can also include medical devices, personalized medicine, and even at-home testing solutions.  
4. Rock Health 2013: at the intersection of healthcare and technology; and not solely in medicine, but across healthcare, including wellness and administration. 
5. Rock Health Definition 2020: What types of platforms are out there? There are already many—and they are continually evolving, with new ones emerging. We expect that state of flux to last for the next few years. Rock Health Definition 2020 Q3 Report: Rock Health defines digital health as the intersection of healthcare and technology. This means that the venture funding tracked only includes technology-enabled health-related companies, whether they focus on the administration of healthcare, the delivery of healthcare, or the process of bringing breakthrough new healthcare products to market (both R&D and commercialization).
6. The Stanford Center for Digital Health: We define digital health broadly, using it to describe digital information or data and communications technologies to collect, share, and manipulate health information to improve patient health and healthcare delivery (Turakhia, Desai, & Harrington, 2016). This definition therefore encompasses a wide variety of software and data technologies (e.g., data science, advanced analytics, artificial intelligence, electronic health records (EHRs), virtual and augmented reality), hardware (e.g., smartphones, tablets, computers, health trackers, wearable technologies, sensors, medical devices), and services or solutions (e.g., video conferencing, mHealth apps, remote monitoring). 
7. Startup Health – What was once defined as “digital health” is converging across all health sectors – in other words: digital health = health.

[Photo above: Left, Edward Braham, Senior Partner at Freshfields Bruckhaus Deringer introduced the speakers and provided the framework for the dialogue]

On October 14, Tim and David Wilkins, in association with Freshfields Bruckhaus Deringer, gathered over 1K community members from around the world to hear their talk on structural racism for both business and legal leaders.

“Over the past few months, organizations have moved the fight for racial justice and equality to the core of their sustainability agendas.  Lawyers and business leaders have a unique and critical role to play in assuring these latest initiatives create sustainable change.”

—Tim Wilkins, Freshfields

The Wilkins brothers, David a Harvard law professor, and Tim, a lawyer/MBA with Freshfields, shared a thoughtful and positive outlook regarding a complex and potentially controversial topic. They provided valuable background on the issues and a realistic sense of urgency during this important window of opportunity to effect positive change. They asked participants to consider playing a role immediately, resulting in this blog. I have confidence that I will be weaving this knowledge and motivation into the way I live and manage, as will those with whom I share this valuable knowledge.

Today, companies can expect new regulations and incentives that will affect race and social injustice. Companies will need to prepare for these changes in advance so that they can be part of the solution going forward. Conversations like those with David and Tim Wilkins can help prepare leaders and citizens alike.

Corporate Social Responsibility (CSR) is a term that has risen to popularity thanks to results many of us have witnessed in our lifetime. Examples include the rise of renewable energy, of the end of the whaling industry, youth advertising of alcohol and tobacco, and other issues that are being affected by regulation of businesses. While there has been remarkable little positive change with regard to race and social justice in the past, thanks to recent developments exposing racial injustice in law enforcement and the health care system, going forward, corporations can expect new regulations regarding racial inequities. Experts like David and Tim Wilkins, can provide both a legal and business perspective that will help companies navigate change so that, as a society, we achieve expected positive outcomes in a timely and effective manner.

Webinar take-aways included:

1. There has been little positive change during the three generations that the Wilkins family has been practicing law (for the last 3 generations, with their father, Julian Wilkins, serving as the first black partner at a major law firm in Chicago in 1971, and their uncle John as the first black professor at the University of Berkeley – see photo below)
2. There is, however, an important opening for change today, as a result of public awareness and compassion regarding inequities in the justice and health care system that were exposed over recent months;
3. There is a growing realization that the investment by businesses in creating positive changes in society can be viable from an economic standpoint. A strategic approach to transparency and following the economic value and incentives will be among factors driving positive change;
4. The legal and business professions need to work together to ensure that policies and procedures are in place that will support the transition in a way that is safe and effective for all stakeholders;
5. The “ask” – that each of us can make a positive change today, no matter how small.

Running 1 hour and 30 minutes, this lecture-dialogue between the Wilkins brothers provides a great roadmap for positive change for the issue of race and social injustice: https://play.freshfields.com/wilkins-brothers-webinar  

Additionally, Freshfields prepared a summary blog, which incorporates key points from a business and legal perspective here.

[Photos below: Webinar screen shot: David Wilkins, the Lester Kissel Professor of Law at Harvard Law School, and Tim Wilkins, Global Partner for Client Sustainability, Freshfields]

[Historical photo: Their father, Julian Wilkins, became the first black partner at a major law firm in Chicago in 1971, and their uncle John was the first black professor at the University of Berkeley.]

[Left, Richit Sihnha, Partner, AV8 Ventures. Right, Glen Tullman Executive Chairman,  Livongo. http://bit.ly/DigtalHealthAI]

Keeping a sharp eye on artificial intelligence will be critical to understanding the future of medicine. 

However, artificial Intelligence (AI)  is often poorly understood, even by business leaders, and yet many consider it part of every aspect of digital health, if not health care overall. What is AI and what are examples of developments that will help us anticipate the future of health care?

According to the Brookings Institute, AI is often poorly understood, even by business leaders. Ai is the use of algorithms that are designed to make decisions, often using real-time data. What makes Artificial Intelligence different from simple programming, is that AI systems are able to handle complex structures like the human body because they learn over time, and become accustomed to increasingly complex sets of input. There is not just one action for every input, but the actions are adjusted by a myriad of factors, and the way the system adjusts is affected by what it learns over time as well.

During the recent 2020 Digital Health Awards, “New Application of AI” was one of about one dozen award categories. However, it seems that AI will soon be an aspect of all elements of digital health, and health care in general, for that matter. According to Richit Sihnha, Partner, AV8 Ventures, “AI will be as transformative to the healthcare industry as sequencing was for the diagnostics and therapeutics industry.” She believes that, some day, “AI will be core to everything we build in health care.”

Glen Tullman Executive Chairman,  Livongo, a company that uses convenient monitoring devices, call/text centers and computer algorithms to personalize diabetes care, described AI in terms its effect on peoples’ lives rather than on the technology itself.  Tullmann talked about people and magic, referencing a quote by science writer Arthur C. Clark, who said, “Any sufficiently advanced technology is indistinguishable from magic.’” Tullman underscored this point, adding, “We can use technology …and data science to create magical experiences, and we can really make it easier for people to stay healthy. That’s why this excites me!” In July 2019, Livongo went public, and September 2020, announced an $18.5B merger with Teledoc, the largest digital health deal in history. Going forward,  the company anticipates further developments in its vision to deliver life-changing services.

Chris Manzi, MD, Co-founder and CEO at Viz.ai, with audiences the role of AI in saving those who have had a stroke. Time is critical to patient outcomes in stroke care. AI in radiology can be used to reduce treatment time by automating radiology reads to diagnosis a stroke before a human has read the scan. During the CT exam, when the patient is first being imaged (the first step of the process) if the algorithm indicates a possible stroke, the entire care team, from the radiologists and neurologist quickly come together to verify the AI diagnosis and the surgical plan. In the past, each specialist would see the patient sequentially, a 2-hour process. By working in unison once alerted, the total time to treatment is less than one hour after the CT scan.  Thanks to the impact of Viz.Ai in treating stroke patients, they received the first clearance for the application of AI in healthcare by the FDA. Further, in September 2020, they became the first AI software to receive a Medicare New Technology Add-on Payment so that hospitals would be reimbursed for this care, and enabling hospitals adopt advanced technology to improve stroke care. 

For leaders in health care, and those who consume health care, including employers and consumers, staying abreast of this rapidly evolving field will help us evaluate options and manage change in an effective manner. As I look at the marketplace, I will be sorting for those organizations who use their technical capabilities to solve the problems that are most relevant to their customers and those who clearly describe their value proposition. Speaking in ROI terms will be critical to ensuring we can compare one solution to another.

The five companies selected in this manner by a panel of 250 judges at the UCSF Digital Health awards for the “New Applications of AI” include those listed below. Each is worthy of a website visit and a conversation with colleagues to learn more about their technology and the quantitative and qualitative value they offer their customers – both health care professionals and consumers alike.

1. Livongo – Personalizing diabetes care (UCSF Digital Health AI Award-winner 2019)
2. Viz.Ai – Accelerating stroke care by automating the analysis of stroke care (UCSF Digital Health Award-winner 2020)
3. Suki Health – 100% accurate voice dictation to liberate physicians from note-taking
4. Gauss Surgical – Powering surgical and maternal safety with A.I.
5. Karius – Blood test based on next-generation sequencing of microbial cell-free DN.

For more information on the the “New Application of AI” category, scroll to minute 17:11  here: bit.ly/DigtalHealthAI   

UCSF Health Hub recently hosted the 2nd annual UCSF Digital Health awards. The initial vision, as Mark Goldstein, founder, pointed out, was to define an industry to allow it to achieve its true potential in terms of collaboration, relationships and funding. UCSF Health Hub is clearly creating the connections across life sciences, technology, and the investment community to enable the advances that our industry needs. The end-game is to make health care more affordable and accessible, and to ensure that the 10-year gains made during the last 6 months during COVID continue to advance. 

In the months leading up to the awards ceremony, the team assembled 750 applicants, 250 judges, and 120 speakers and thousands of audience members representing diverse perspectives. This process resulted in winners in each of 15 distinct categories, including those that were defined by a technology (i.e. AI), a health outcomes (i.e. mental health), addressing an access (i.e. cost savings) and affiliation-specific contributions to the field by UCSF. Net-net, they gave us a platform to understand how the industry is defined, as well as an introduction to the thought-leaders and the companies who are recognized as having make significant contributions to the field to-date. It is critical that each of us, as business leaders, providers, policy-makers and/or consumers, understands the important developments happening at the interface between technology and health care in the weeks and months ahead. In taking a proactive role, we will be able to help ensure that positive change gains momentum. It is clear that our collective voices are needed to ensure that digital health does not lose ground post-COVID. 

Among the 15 categories recognized at the ceremony* (see below), most (7) related to health outcomes (mental health, wellness, prevention, etc.), one addressed patient access issues (patient cost savings), and one recognized a technology type (application of AI). Additionally, two also spotlighted UCSF-specific contributions to the field (i.e. Best technology with UCSF DNA).

In the coming days, I looking forward to delving into the results of the following four sub-categories to learn more about the leaders, vision and impact that each team has had on our industry who each had remarkable insights to share during the awards ceremony:  (1) New application of AI, where the winner was Viz.ai, (2) Remote Diagnostics, where the winner was Conversa Health; (3) Mental and Behavioral Health, where the winner was Ginger; and (4) UCSF DNA, where the winner among UCSF applicants was Akili Health.