Constructing the Future of Health

Why the Name Matters

Defining the Mission Behind the Tagline

The new tagline, Constructing the Future of Health with Data-Driven Tools, captures both the precision of the field and the pragmatism of its faculty.

“It directly defines our mission: to build tools on data, to improve health,” said Shah.
“It conveys our commitment to translating data into tangible solutions that advance care,” added Lee.

Desai explained that the shift also repositions the division squarely within medicine. “While biomedical informatics traditionally emphasized data systems and information management,” she said, “computational medicine underscores the use of quantitative science — biostatistics, computation, and modeling — as drivers of clinical discovery and decision-making.”

Purvesh Khatri, PhD, Professor of Medicine in Biomedical Informatics at the Research Institute for Immunity, Transplantation and Infection, agreed. “Biomedical informatics tends to stop short of clinical translation,” he said. “Computational medicine implies the full continuum, from data to practice to delivery.”

“Our division has been remarkably successful in developing technology that is used widely in the clinical arena and in the laboratory,” Musen added. “Our faculty members can point to many thousands of users for their contributions, and it’s a distinguishing feature of our group.”

Translational Impact

Inside the division, that continuum is already taking shape.

A major goal for Desai’s team is to design studies with clinical investigators that will be impactful and informative. To that end, the team is building StatChat, a suite of tools designed by statisticians and for statisticians to make rigorous, ethical statistical practice more efficient. Her group has also developed novel frameworks for evaluating AI-supported interventions, redefining what a clinical trial can look like. “Our approach has transformed how trials are performed,” she said. “A diabetes management program we evaluated in this framework is now part of Stanford’s healthcare system and continually refined in real time.”

Shah’s data science team leads the development of ChatEHR, a generative AI platform that enables use of language models directly in clinical workflows. It is available to over 5000 physicians and nurses for interacting with a patient’s complete medical record, to summarize the record, draft documentation for patients or insurers, identify care gaps as well as automate rote tasks, while preserving privacy and institutional control.

Chen’s group studies how computational tools intersect with human clinical judgment. His team’s SmartAlert framework takes that insight directly to the bedside. The system continuously analyzes streams of clinical data to anticipate diagnostic or treatment needs, surfacing timely, evidence-based recommendations tailored to each patient’s situation. Already being rolled out across the hospital, SmartAlert helps clinicians act earlier and with greater precision than traditional rule-based systems could provide.

Khatri pointed to the TriVerity test as another example of clinically grounded innovation. The quick blood test turns complex lab data into three easy-to-read scores that help doctors decide, in real time, whether a patient has an infection, how severe it is, and whether they may soon need intensive care. “Because we’re embedded in medicine, we knew the real question wasn’t just ‘Does this patient have sepsis?’” Khatri said. “It was, ‘Does the patient have an infection, and how serious is it?’ That nuance guided the design.”

Musen’s group contributes foundational infrastructure that powers these innovations. “Protégé, a tool developed in our lab, is now the primary way people build controlled vocabularies in biomedicine,” he said. “It’s what the National Cancer Institute uses to define cancer terms and what the World Health Organization uses to build the latest global disease classification system.”

Collaboration as Core Infrastructure

The new identity also reflects how the division works. “Modern biomedical problems are too complex for any single discipline,” said Desai. “The success of our projects rely on multiple perspectives – e.g., oncologists, pathologists, biostatisticians, and computational biologists on one team with shared goals. These collaborations expose new methodological gaps that push the science forward.

For Shah, location matters. “Roughly seventy percent of patients seen at Stanford Health Care are cared for by our department’s faculty,” he said. “That gives us a direct bridge between data science and clinical practice.”

As Chen puts it, “Innovation happens at the interfaces — but only when people truly understand both sides.”

Musen emphasized the same point: “Virtually everything we do is interdisciplinary. All of our projects involve team science, and our position in the Department of Medicine gives us ready access to clinicians and bench scientists eager to collaborate.”

Looking Ahead

When asked what the “future of health” looks like, faculty members offered a piece of a shared vision:

• Desai sees “care decisions optimized and driven by rigorous evidence.”

• Lee imagines “data-driven decisions that are precise, equitable, and personalized.”

• Khatri envisions “a continuous feedback loop between science, practice, and delivery.”

• Chen foresees “the democratization of expertise: new forms of care mediated or delivered by AI systems that would once have seemed impossible.”

• Musen shared, “Computational medicine will accelerate the ways biomedical research informs clinical decision-making. By revolutionizing how we collect, disseminate, and use experimental data, we can speed the delivery of new results into the clinical arena to improve health in concrete ways.”

As the division celebrates its new chapter at the December rebranding event, that vision feels within reach. “Computational Medicine is more relevant and collaborative than ever,” said Lee. “It’s both recognition and renewal.”

Khatri calls it “a testament to the division’s adaptability and leadership in advancing science, practice, and delivery,” while Chen adds, “This rebrand lets us finally say, in plain language, what we’ve been doing all along — building the computational foundations of modern medicine.”