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
Amazon
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
DeepScribe
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
Verily
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