Current Projects

Below is a list of our ongoing collaborations with both internal and external organizations working on healthcare AI implementations. Read and view relevant articles and presentations stemming from our collaborations using the button below.

External Collaborations


Natural Language Processing in Medicine

Co-designed the "NLP in Medicine" workshop for the 58th Annual Meeting of the Association for Computational Linguistics in July 2020

American Academy of Family Physicians (AAFP)

AI in Primary Care

Identifying high value projects to advance AI and ML solutions to critical challenges in primary care and mentoring physician innovators through the AAFP Primary Care Innovation Fellowship


Reducing Administrative Burden with Technology

Advising the AAFP on the role of emerging technologies in its Administrative Burden Reduction Plan

American Board of Artificial Intelligence in Medicine (ABAIM)

AI Education

Advancing understanding and application of AI in clinical medicine through education and certification of healthcare professionals with ABAIM

American Board of Family Medicine (ABFM)

AI Research in Primary Care

Setting a national research agenda for AI and ML in primary care, and building capacity for AI/ ML research within departments of family medicine across the country through a collaboration with ABFM and the Center for Professionalism & Value in Health Care

Codex Health

Risk Stratification & Prediction

Studying the feasibility and acceptability of a medical analytics platform powered by machine learning and natural language processing to deliver capabilities spanning population health, cohort discovery, predictive analytics, remote patient monitoring, and clinical decision support with Codex Health


Remote Patient Monitoring

Assessing the current landscape of remote patient monitoring tools and technologies to determine the key features of success and needs that remain unmet


AI-Powered Scribe

Co-designed and conducted a survey with DeepScribe to explore provider experiences and attitudes towards emerging technologies that aim to assist providers by automating certain aspects of clinical documentation

Google Health

AI in Care Delivery

Exploring the utility and promise of applying AI to healthcare, including technology-enabled documentation and tools to support care delivery with Google Health


Care Planning

Designing and assessing the acceptability of an AI-enabled model for pre-visit planning and intra-visit care management in primary care


Interpreting Skin Conditions with AI

Researching the feasibility and acceptability of an AI-powered tool to assist primary care providers with classifying and assessing skin conditions

Gordon and Betty Moore Foundation

National AI Steering Committee

Advising GBMF on the purpose and structure of a national coordinating center and grant program to advance the implementation and prospective evaluation of AI/ML diagnostic decision support tools to improve patient care and diagnostic outcomes

Omada Health

Remote Patient Monitoring Evaluation

Collaborating with Omada Health on a pragmatic trial testing the hypothesis that commercial patient-facing digital care platforms can be intentionally and effectively paired with health systems to augment the primary care of patients with chronic conditions such as hypertension, diabetes, and depression

Predicta Med

Early Detection of Autoimmune Disease

Validating a machine learning tool for identifying patients with an undiagnosed autoimmune disease one year prior to first recorded diagnosis with Predicta Med

Quadrant Technologies

Reimagining Patient Portals with AI 

Designing and building an AI-powered system to automate the sorting and routing of patient messages as a first step towards reimagining patient portals and reducing the burden of the inbox on clinicians


Predicting and Preventing Harm in the Hospital

Retrospectively validating a suite of AI-enabled tools predicting infections and other adverse events in the inpatient setting (e.g. sepsis and falls with injury) to prepare for a prospective pilot and evaluation of the impact on patient outcomes and provider workflows

SOAP Health

AI Medical Interviewing, Risk Assessment, and SOAP Note Creation

Studied the feasibility and acceptability of a conversational AI for pre-visit medical interviews with SOAP Health

Society of Teachers of Family Medicine (STFM)

Telemedicine Education

Developed a national telemedicine curriculum for medical students, residents, and teaching clinicians as part of STFM's National Telemedicine Task Force


UCSF Center for Clinical Informatics and Improvement Research (CLIIR)

Data and Technology to Support Diagnostic Excellence

Developed a whitepaper with CLIIR that investigates potential investments in artificial intelligence to advance diagnostic excellence for the Gordon and Betty Moore Foundation


Medical Device Innovation

Collaborating with Verily on multi-site investigational studies assessing the feasibility of new investigational devices designed to estimate blood pressure and cardiac filling pressure

Stanford Collaborations

Center for Artificial Intelligence in Medicine & Imaging (AIMI)

Closing Gaps in Healthcare AI

Identifying and addressing gaps and barriers in the field of healthcare AI with the goal of accelerating and streamlining the translation of AI tools for clinical applications with AIMI

Center for Automotive Research (CARS)

Detecting Providers' Stress Levels

Assessed the feasibility and efficacy of detecting stress in family medicine practitioners through desktop computer interactions with CARS

Center for Biomedical Informatics Research (BMIR)

Enabling Advance Care Planning Discussions

Implemented a predictive mortality model to enable patient selection for end of life advance care planning discussions and increased the incidence of documented conversations at Stanford Health Care with BMIR


AI-Driven Order Recommendations

Developing AI-driven clinical order recommendations for primary care physicians to tee up appropriate and efficient specialty care consultations

Center for Digital Health (CDH)

AI in Hypertension Management

Consulting on CDH's development of an AI-powered hypertension management algorithm for cardiologists and primary care physicians

Clinical Excellence Research Center (CERC)

Computer Vision Depression Screening

Studying the feasibility of developing an AI algorithm that can predict depression and anxiety based on audio and visual cues captured from a recording of the person with CERC


Insulin-Dependent Diabetes Management

Advising a project assessing the feasibility and acceptability of leveraging at-home voice applications to assist patients with insulin-dependent diabetes management remotely

Evaluation Sciences Unit (ESU)

AI in Pre-Visit Planning

Completed a comprehensive environmental scan, a literature review, and key informant interviews to explore the use of AI in pre-visit planning with the ESU

Master of Science in Clinical Informatics Management (MCiM)

Master of Science in Clinical Informatics Management

Collaborating with MCiM - a master's program for working professionals seeking to harness the power of digital innovations in healthcare - to provide a management-focused educational experience and foster digitally-driven excellence in healthcare

Research IT

Clinical Identification Tools

Developing high-performance open source clinical identification tools that enable researchers around the world to use clinical text for AI-driven applications while preserving patient privacy with Research IT

Stanford Health Care

Detecting Inpatient Clinical Deterioration

Implementing a predictive model for clinical deterioration in the inpatient acute care setting to reduce unexpected escalations to the intensive care units and mortality at Stanford Health Care and Valley Care

Stanford Institute for Human-Centered AI (HAI)

AI + Healthcare Global Conference

Co-designed sessions for the Stanford AI + Health Global Conference covering topics related to AI applied research, academic partnership with industry, as well as equity and community engagement in health AI

Stanford Medicine Center for Improvement (SMCI)

Improvement Across Stanford Medicine

Collaborating with SMCI as active affiliate faculty and guest lecturers in order to foster a culture of continuous improvement across Stanford Medicine

Stanford Prevention Research Center (SPRC)

Remote Patient Monitoring and AI Health Coaching

Designing a large pragmatic trial of a comprehensive digital care platform versus usual care for the treatment of hypertension with SPRC

Stanford WellMD & WellPhD Center

Reimagining Patient Portals with AI

Partnering with WellMD & WellPhD to develop an AI-powered system to automate the sorting and routing of patient messages as a first step towards reimagining patient portals and reducing the burden of the inbox on clinicians

Join Us

Interested in learning more about our group or collaborating on a project? Visit our contact page to connect with us!