1.7k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of FloridaUS30 papers
- UF Health Cancer Center5 papers
- Cornell UniversityUS4 papers
- Florida CollegeUS4 papers
- Northwestern UniversityUS4 papers
- Stanford UniversityUS4 papers
- Weill Cornell MedicineUS4 papers
- Florida State UniversityUS3 papers
- University of Alabama at BirminghamUS3 papers
- University of California, Los AngelesUS3 papers
- University of California San DiegoUS3 papers
- University of MichiganUS3 papers
34 papers
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science
Betina Idnay, Zihan Xu, William G. Adams +54
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 instituti…
Exploring the Thermostability of CRISPR Cas12b using Molecular Dynamics Simulations
Yinhao Jia, Katelynn Horvath, Santosh R. Rananaware +2
CRISPR (clustered regularly interspaced short palindromic repeat)- based diagnostics are at the forefront of rapid detection platforms of infectious diseases. The integration of re…
Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning
Mengxian Lyu, Cheng Peng, Xiaohan Li +3
Automatic text summarization (ATS) is an emerging technology to assist clinicians in providing continuous and coordinated care. This study presents an approach to summarize doctor-…
Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction
Cheng Peng, Xi Yang, Kaleb E Smith +4
Objective To develop soft prompt-based learning algorithms for large language models (LLMs), examine the shape of prompts, prompt-tuning using frozen/unfrozen LLMs, transfer learni…
A Study of Generative Large Language Model for Medical Research and Healthcare
Cheng Peng, Xi Yang, Aokun Chen +16
There is enormous enthusiasm and concerns in using large language models (LLMs) in healthcare, yet current assumptions are all based on general-purpose LLMs such as ChatGPT. This s…
MicroSegNet: A Deep Learning Approach for Prostate Segmentation on Micro-Ultrasound Images
Hongxu Jiang, Muhammad Imran, Preethika Muralidharan +12
Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides 3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost, accurate di…
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension
Cheng Peng, Xi Yang, Zehao Yu +3
Objective: To develop a natural language processing system that solves both clinical concept extraction and relation extraction in a unified prompt-based machine reading comprehens…
Contextualized Medication Information Extraction Using Transformer-based Deep Learning Architectures
Aokun Chen, Zehao Yu, Xi Yang +3
Objective: To develop a natural language processing (NLP) system to extract medications and contextual information that help understand drug changes. This project is part of the 20…
SODA: A Natural Language Processing Package to Extract Social Determinants of Health for Cancer Studies
Zehao Yu, Xi Yang, Chong Dang +12
Objective: We aim to develop an open-source natural language processing (NLP) package, SODA (i.e., SOcial DeterminAnts), with pre-trained transformer models to extract social deter…
A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models
Zehao Yu, Xi Yang, Chong Dang +8
Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, fa…
Age-Stratified COVID-19 Spread Analysis and Vaccination: A Multitype Random Network Approach
Xianhao Chen, Guangyu Zhu, Lan Zhang +3
The risk for severe illness and mortality from COVID-19 significantly increases with age. As a result, age-stratified modeling for COVID-19 dynamics is the key to study how to redu…
A Simulation Study Evaluating Phase I Clinical Trial Designs for Combinational Agents
Shu Wang, Ji-Hyun Lee
Nowadays, more and more clinical trials choose combinational agents as the intervention to achieve better therapeutic responses. However, dose-finding for combinational agents is m…
Joint Distribution and Transitions of Pain and Activity in Critically Ill Patients
Florenc Demrozi, Graziano Pravadelli, Patrick J Tighe +2
Pain and physical function are both essential indices of recovery in critically ill patients in the Intensive Care Units (ICU). Simultaneous monitoring of pain intensity and patien…
Federated Learning for Healthcare Informatics
Jie Xu, Benjamin S. Glicksberg, Chang Su +3
With the rapid development of computer software and hardware technologies, more and more healthcare data are becoming readily available from clinical institutions, patients, insura…
IFAA: Robust association identification and Inference For Absolute Abundance in microbiome analyses
Zhigang Li, Lu Tian, A. James O'Malley +8
The target of inference in microbiome analyses is usually relative abundance (RA) because RA in a sample (e.g., stool) can be considered as an approximation of RA in an entire ecos…
Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods
Xi Yang, Yan Gong, Nida Waheed +4
Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment outcomes and quality of life. Early detection of cancer patients at risk for car…
Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World
Julianna D. Ianni, Rajath E. Soans, Sivaramakrishnan Sankarapandian +9
Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin \& eosin stained tissue by a pathologist. Areas of high inter-pathologist…
Understanding Perceptions and Attitudes in Breast Cancer Discussions on Twitter
Francois Modave, Yunpeng Zhao, Janice Krieger +5
Among American women, the rate of breast cancer is only second to lung cancer. An estimated 12.4% women will develop breast cancer over the course of their lifetime. The widespread…
Enhancing Prediction Models for One-Year Mortality in Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome
Seyedeh Neelufar Payrovnaziri, Laura A. Barrett, Daniel Bis +2
Predicting the risk of mortality for patients with acute myocardial infarction (AMI) using electronic health records (EHRs) data can help identify risky patients who might need mor…
Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program
Michael P Snyder, Shin Lin, Amanda Posgai +22
Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years,…
Building Computational Models to Predict One-Year Mortality in ICU Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome
Laura A. Barrett, Seyedeh Neelufar Payrovnaziri, Jiang Bian +1
Heart disease remains the leading cause of death in the United States. Compared with risk assessment guidelines that require manual calculation of scores, machine learning-based pr…
Learning Gene Regulatory Networks with High-Dimensional Heterogeneous Data
Bochao Jia, Faming Liang
The Gaussian graphical model is a widely used tool for learning gene regulatory networks with high-dimensional gene expression data. Most existing methods for Gaussian graphical mo…
Comparing Clinical Judgment with MySurgeryRisk Algorithm for Preoperative Risk Assessment: A Pilot Study
Meghan Brennan, Sahil Puri, Tezcan Ozrazgat-Baslanti +6
Background: Major postoperative complications are associated with increased short and long-term mortality, increased healthcare cost, and adverse long-term consequences. The large…
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models
Subhabrata Majumdar, George Michailidis
The rapid development of high-throughput technologies has enabled the generation of data from biological or disease processes that span multiple layers, like genomic, proteomic or…