This $375,964 Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program aims to address the issues of factual inaccuracy and unfaithful reasoning in large language models (LLMs) applied to biomedical and healthcare domains. The key objectives are to: (1) establish a self-augmentation framework to enable LLMs to automatically select and use relevant biomedical digital resources; (2) develop an LLM curator...
This Project Grant award from the National Institutes of Health (NIH) under the Medical Library Assistance (CFDA 93.879) program provides $351,000 to the University of Texas Health Science Center at Houston (UTHealth) from September 16, 2024 to August 31, 2028. The funding supports research to develop a trustworthy and high-performance question answering system for electronic health records (EHRs). The project aims to combine large language models with a carefully-designed system called Quehry...
This Project Grant award from the National Institute of Environmental Health Sciences (NIEHS), under the Medical Library Assistance (CFDA 93.879) federal grant program, will fund the development and validation of a clinically reliable and transparent large language model (LLM)-based question-answering (QA) system and a clinical chatbot for decision support in emergency department (ED) settings. The total funding amount is $176,068.00, with an award date of September 1, 2024, and an expected...
This federal Project Grant award for $1,312,212 from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program will support research to develop an advanced DNA language model. The primary goal is to use natural language processing techniques to better understand the role and functionality of DNA sequences, especially non-coding regions, which could lead to advancements in areas like genetic testing and personalized medicine. The...
The National Institute of Environmental Health Sciences (NIEHS) has awarded a $351,000 Project Grant under the Medical Library Assistance (CFDA 93.879) program to the University of Texas Health Science Center at Houston (UTHealth). The grant aims to develop an integrated deep learning model to optimize the 5' untranslated region (UTR), codon usage, and 3' UTR of mRNA sequences. This work is intended to enhance the protein expression level and improve the efficacy of mRNA medicines, which have...
This $962,930 Project Grant award from the National Institute of Standards and Technology (NIST) under the Congressionally-Identified Projects program (CFDA 11.617) supports research at the University of Texas at Dallas (UTD) to address challenges in the reliability, security, and privacy of AI models, particularly in healthcare applications. The key activities include: Developing techniques to evaluate prompts and detect harmful or malicious use of large language models (LLMs) Investigating...
This Project Grant award from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), provides $314,363 to Delineate Inc. to develop an innovative platform that uses large language models (LLMs) to accelerate the building and repurposing of quantitative systems pharmacology (QSP) models from scientific literature. The key objectives are to: (1) develop an LLM-powered platform for efficient QSP model construction...
This Project Grant award of $348,227 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at the University of Delaware to improve the scalability and effectiveness of large language models (LLMs) for healthcare applications. The key objectives are to develop methods for evaluating LLM performance and mitigating issues with incomplete data, ensuring truthful and transparent LLM outputs. The research also integrates...
This Project Grant award of $367,876 from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program supports research to develop robust Bayesian adaptive designs and methods for multi-arm, multi-dose, multi-stage platform clinical trials. The research aims to address practical challenges in real-world platform trials, such as optimizing sequential monitoring, establishing proof-of-concept and dose selection, managing...
This $729,821 Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program supports the development of artificial intelligence (AI) and machine learning (ML) methods for real-time monitoring and updating of clinical decision support (CDS) systems. The goal is to reduce health disparities that may arise from the use of CDS tools. The key products of this work include: Fair ML models trained on retrospective...