Zhe He

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Assistant Professor

Florida State University

United States

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About

Dr. Zhe He is an Assistant Professor at Florida State University, United States. His research areas include the application of large language models for healthcare, cognitive training adherence, and the use of machine learning techniques to enhance patient care and engagement. Recent articles authored by Dr. He focus on improving summarization accuracy in medical contexts and evaluating the quality of generative models in interpreting laboratory test results for lay patients.

Recent Grants

Grant: Close

Prediction of Health Outcomes and Adverse Events in Pediatric Organ Transplantation in Florida

Open Date: 2022-02-10

Close Date: 2024-01-31

Grant: Close

The Adherence Promotion with Person-centered Technology (APPT) Project: Promoting Adherence to Enhance the Early Detection and Treatment of Cognitive Decline

Open Date: 2019-08-01

Close Date: 2024-03-31

Grant: Close

Systematic Analysis of Clinical Study Generalizability Assessment Methods with Informatics

Open Date: 2019-01-15

Close Date: 2020-11-30

Grant: Close

Together: Transforming and Translating Discovery to Improve Health

Open Date: 2015-08-15

Close Date: 2024-06-30

Articles (16)

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2025

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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Professor and Director

Medical College of Wisconsin

UNITED STATES

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Zhe He

Research Interests

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Contact this professor

About

Recent Grants

Articles (16)

Improving Large Language Models’ Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation

Ontology enrichment using a large language model: Applying lexical, semantic, and knowledge network-based similarity for concept placement

Enhancing patient engagement and understanding: is providing direct access to laboratory results through patient portals adequate?

Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

New opportunities for the early detection and treatment of cognitive decline: adherence challenges and the promise of smart and person-centered technologies

Motivation to Engage in Aging Research: Are There Typologies and Predictors?

A Machine-Learning Based Approach for Predicting Older Adults’ Adherence to Technology-Based Cognitive Training

Assessing the use of prescription drugs and dietary supplements in obese respondents in the National Health and Nutrition Examination Survey

Understanding Information Needs and Barriers to Accessing Health Information Across All Stages of Pregnancy: Systematic Review

User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study

Exploring the feasibility of using real-world data from a large clinical data research network to simulate clinical trials of Alzheimer’s disease

How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov

Machine learning–based prediction of health outcomes in pediatric organ transplantation recipients

Collaborators (7)

Navya Martin Kollapally

Dawn Carr

Muhammad Amith

Mia Liza A. Lustria

BALU BHASURAN

Hao Liu

William Hogan

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