Dr. Joe Xing · joexing.me
Unlocking Clinical Data with AI: The Rise of Large Clinical Language Models
LLM Day — Large Language Models, AI & ML · Harness, San Francisco, United States · April 16, 2026
Abstract
Modern clinics generate vast amounts of data, from biomarker tests and imaging to functional assessments and patient symptom profiles, yet much of it remains underutilized. This talk explores how Large Clinical Language Models (LCLMs) can transform fragmented clinical data into structured, actionable intelligence. By integrating diverse clinical signals, LCLMs enable comprehensive patient representations and deliver insights directly at the point of care. Drawing from real-world deployments, we highlight how AI can augment clinician decision-making and unlock the full value of clinical data for more personalized, precise care.
FNC NeuroRecharge Research Collaboration Week at The Functional Neurology Center
The Functional Neurology Center · Minnetonka, MN · February 26, 2026
Abstract
FNC NeuroRecharge Research Collaboration Week brought together clinicians, researchers, and collaborators to present how advanced AI systems are being developed to automate and enhance research workflows, including intelligent processing of clinical scribes, provider notes, and patient-reported forms. The event highlighted applications of computer vision for gait and movement analysis using walking video data, alongside multimodal AI frameworks connecting textual clinical documentation with MRI neuroimaging, laboratory biomarkers, and symptom-driven datasets such as MARCoNS testing, mycotoxin exposure markers, and vestibular rehabilitation outputs including VOR and OKP data. NeuroRecharge represents an important step toward building scalable neuroscience research infrastructure that supports collaboration, publication, and the future of personalized brain health.
From Large Language Models to Agentic AI: Transforming Medical Imaging and Healthcare
Tsinghua University · Beijing, China · September 16, 2025 · Host: Prof. Liming Zhang
Abstract
Modern clinics generate vast amounts of data, from biomarker tests and imaging to functional assessments and patient symptom profiles, yet much of it remains underutilized. This talk explores how Large Clinical Language Models (LCLMs) can transform fragmented clinical data into structured, actionable intelligence. By integrating diverse clinical signals, LCLMs enable comprehensive patient representations and deliver insights directly at the point of care. Drawing from real-world deployments, we highlight how AI can augment clinician decision-making and unlock the full value of clinical data for more personalized, precise care.
An End-to-end Deep Learning Based Disease Prediction Framework — Case Study: Mild Cognitive Impairment
Defeating Dementia: New Directions from The Biology of Aging · Alzheimer’s Drug Discovery Foundation (ADDF) · Bakar Labs, Berkeley, CA · April 13, 2023
Early Prediction of Multiple Sclerosis Using Scanning Laser Ophthalmoscopy (SLO) Video Sequence Data with a Deep Learning Based Approach
Optica Fall Vision Meeting · University of Rochester, Center for Visual Science · Rochester, NY · October 21–23, 2022
A Data-driven Human Behavior Learning System to Coach Self-driving Cars
4th Annual Global Artificial Intelligence Conference · Santa Clara, CA · January 21, 2020
Predicting Short-term Driving Intention Using Recurrent Neural Network on Sequential Data
Intel & O’Reilly Artificial Intelligence Conference — Put AI to Work · San Francisco, CA · September 7, 2018
Applications of Deep Neural Network (Invited Talk)
Tsinghua University · Beijing, China · September 13, 2017
Radiation Damage Effects in the LHCb Vertex Locator (Invited Talk)
22nd RD50 Workshop · Albuquerque, NM · June 3, 2013
Early Prediction of Multiple Sclerosis Using Scanning Laser Ophthalmoscopy (SLO) Video Sequence Data with a Deep Learning Based Approach
ECTRIMS · Amsterdam, Netherlands · October 26–28, 2022
Retinal Task Detection and Image Perception Using End-to-end Deep Neural Network Based Algorithms
ARVO Annual Meeting · Denver, CO · June 2022 · Vol. 63, Issue 7
X-ray Diffraction at Matter in Extreme Conditions Endstation
57th Annual Meeting of the APS Division of Plasma Physics · Savannah, GA · November 16–20, 2015
Deep Active Learning Using Scanning Laser Ophthalmoscopy Image Embedding Vectors to Optimize Training Data Selections
Optica Fall Vision Meeting · University of Rochester, Rochester, NY · October 21–23, 2022 · Presenter: Yifan Zhang
Automated System for Template Matching Using SLO Images
2026 ARVO Annual Meeting · May 7, 2026 · Session: Machine Learning for Classification, Segmentation and Others · Poster #5201-0264 · Presenter: Emily Chen