Artificial Intelligence / Machine Learning Demonstration Projects 2025

Crowdsourcing ideas to bring advances in data science, machine learning, and artificial intelligence into real-world clinical practice.

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Proposals (41 total)

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AI Chatbot Integration into APeX MyChart for Enhancing Patient Education and Reducing Provider Burden in Chronic Autoimmune Disease

Submitted by Pritikanta Paul on April 6, 2025 - 7:13am Last revised by Zeanid Noor on April 30, 2025 - 4:15pm.
Proposal Status: 
In Review

This project aims to integrate an AI chatbot into APeX MyChart to enhance patient education, while reducing provider burden to respond to myChart messages in managing chronic autoimmune diseases. The first pilot implementation will focus on Myasthenia Gravis (MG), providing patients with personalized, accessible information and support. The AI chatbot will help answer patients' questions regarding the disease. By improving patient knowledge and confidence about their condition, the chatbot aims to empower patients and improve health outcomes while reducing provider burnout. The project team includes as PI, a neuromuscular neourologist who runs an MG clinic and a co-PI who is an expert in technology-mediated persuasive communications, especially in medical and healthcare settings. Following a sucessful pilot, we would open the infrastructure to extend the AI chatbot to other chronic autoimmune conditions, such as ALS and possibly Rhuematoid Arthritis leveraging its success to benefit a broader patient population.

AI-Driven Endometriosis Symptom and Risk Assessment Tool for Personalized Patient Management

Submitted by Jeannette Lager on April 6, 2025 - 1:26am Last revised by Zeanid Noor on April 30, 2025 - 4:15pm.
Proposal Status: 
In Review

The UCSF Health Problem: Endometriosis is a chronic, debilitating condition affecting approximately 10% of reproductive-age women worldwide. It is characterized by the growth of endometrial-like tissue outside the uterus, leading to severe pelvic pain, dysmenorrhea, dyspareunia, bowel and bladder dysfunction, and infertility. Despite its prevalence, endometriosis remains significantly underdiagnosed, resulting in profound patient suffering and substantial economic burden.

Implementation of an AI-Powered Platform for Scalable, Real-Time Lab Monitoring in Immunosuppressive Treatment

Submitted by Augusto Garcia Agundez Garcia on April 5, 2025 - 9:36pm Last revised by Zeanid Noor on April 30, 2025 - 4:18pm.
Proposal Status: 
In Review

1. The UCSF Health Problem

Adaptive closed-loop large language model platform to improve imaging surveillance of intracranial tumors

Submitted by Ramin Morshed on April 1, 2025 - 8:41pm Last revised by Ramin Morshed on April 30, 2025 - 5:31pm.
Proposal Status: 
In Review

1. The UCSF Health problem: Imaging surveillance represents a cornerstone of brain tumor management and includes surveillance of incidental lesions that may require future treatment or post-treatment follow-up to ensure disease control. Intracranial lesions are relatively common on magnetic resonance imaging and are incidentally seen in 0.7-1.6% of the general population 1,2. These typically include “benign” tumors that are slow growing and may require years of follow-up.

AI-Enhanced Clinical Decision Support Tool to Personalize HIV Treatment and Address Care Delivery Gaps

Submitted by Jose Gutierrez on April 6, 2025 - 11:01pm Last revised by Leslie Yuan on April 30, 2025 - 8:56am.
Proposal Status: 
In Review

Section 1. The UCSF Health Problem. Despite major advancements in antiretroviral therapy (ART), challenges remain for people with HIV (PWH) who are sub-optimally engaged in care due to treatment misalignment, stigma, unstable housing, mental health needs, and other barriers that compromise adherence.1,2 Clinical decisions often follow standardized protocols, overlooking patient preferences and psychosocial factors—typically buried in unstructured electronic healthcare record (EHR) notes.

A Multimodal Foundation Model for Enhanced Prostate Cancer Care at UCSF Health

Submitted by Seyed Mansour Abtahi on April 5, 2025 - 11:15pm Last revised by Zeanid Noor on April 30, 2025 - 4:16pm.
Proposal Status: 
In Review

1.  The UCSF Health Problem

Prostate cancer is the most commonly diagnosed malignancy among men in the United States. Accurate diagnosis, staging, and monitoring are critical for effective treatment planning and improving patient outcomes. Imaging modalities, such as Prostate-Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET), CT, and MRI, provide valuable insights but often lack the integration necessary to fully capture the complexity of prostate cancer progression. Current challenges include:

SNAP Into Action: Building an EHR Dashboard to Track Delayed Antibiotic Prescriptions in Pediatric Acute Otitis Media

Submitted by Jessica Pourian on April 2, 2025 - 3:00pm Last revised by Zeanid Noor on April 30, 2025 - 4:35pm.
Proposal Status: 
In Review

The UCSF Health Problem

Automated Knee Osteoarthritis Grading Decision Support Tool

Submitted by Eugene Ozhinsky on April 4, 2025 - 5:13pm Last revised by Zeanid Noor on April 30, 2025 - 4:25pm.
Primary Author: Yuntong Ma
Proposal Status: 
In Review

Plain knee radiographs are a cornerstone in evaluating osteoarthritis (OA), and at UCSF, nearly all such studies include Kellgren-Lawrence (KL) grading to assess severity. While essential, this grading task is repetitive, time-consuming, and inherently subjective—especially in borderline cases. In fact, studies show only moderate inter-reader reliability in KL grading, creating inconsistencies in diagnosis and downstream care decisions. KL grading adds to radiologist workload, reducing time available for complex cases and clinical consults. We propose integrating an automated AI model for KL grading directly into the radiology workflow at UCSF. By deploying this AI system at the point of care, we can support more efficient workflows, better diagnostic consistency, and enhanced trainee learning.

 

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