Informatics tools to improve the interpretability and interoperability of informed consent instruments
75N91020C00017 (NIH) | Cui Tao (PI), Amy Franklin (Co-I), Muhammad Amith (Co-I)
09/16/2020 – 06/15/2021
This project addresses the permissions statements in consent forms, starting with permissions for collection, sharing, and reuse of specimens and associated data. Specifically, we aim to build a prototype of an application that leverages semantic metadata about permissions in consent forms, and to identify participant friendly terminology for permissions that can be linked to Informed Consent Ontology terms with the same meaning, facilitating computability and strong linkages with other terminology systems.
Using big data and deep learning on predicting HIV transmission risk in MSM population
1R56AI150272 (NIH) | Cui Tao, Kayo Fujimoto, John Schneider (MPI)
09/01/2020 – 08/31/2021
The goal of this project aims at predicting HIV transmission risks using advanced informatics approaches.
Dynamic learning for post-vaccine event prediction using temporal information in VAERS
R01AI130460 (NIH) | Cui Tao (PI), Yong Chen (MPI)
02/01/2017 – 01/31/2022
The goal of this project is to develop novel informatics and statistical approaches for dynamically predicting adverse effects post vaccination.
Artificial Intelligence-aided personalization on dual antiplatelet therapy for patients underwent coronary stent implementation using large-scale Electronic Health Records
19GPSGC35180031 (AHA) | Cui Tao (PI)
12/01/2019 – 11/30/2023
In this project, we will develop and validate novel deep learning methods for evaluating the risk of bleeding and ischemic events (e.g. life-threating bleeding, thrombosis and myocardial infarction) after coronary artery stent implantation so as to suggest personalized DAPT duration through learning pattern from large-scale electronic health records.
Facilitate observational studies of Alzheimer's Disease and Alzheimer's Disease-related dementias using ontology and Natural Language Processing
R1RF1AG072799 (NIH) | Hua Xu, Cui Tao, and Hongfang Liu (Mayo Clinic) (MPI)
05/01/2021 - 04/30/2024
This project will develop novel ontology and natural language processing (NLP) methods and tools to extract and standardize clinical information for observational Alzheimer's Disease/Alzheimer's Disease-Related Dementias (AD/ADRD) research.
An informatics framework for SUDEP risk marker identification and risk assessment
R01NS116287 (NIH) | Licong Cui (PI)
05/15/2020 - 04/30/2025
The main goal of this project is to develop a SUDEP Risk Marker Extraction system for automated extraction of known and putative SUDEP risk markers from the multimodal patient data collected by the Center for SUDEP Research from Epilepsy Monitoring Units in multiple medical centers.
An ontology-driven faceted query engine for the Kentucky Cancer Registry
R21CA231904 (NIH) | Licong Cui & GQ Zhang (MPI)
06/06/2018 - 07/31/2021
The main goal of this project is to develop OncoSphere, a novel ontology-driven faceted query system to enhance web-based exploration of Kentucky Cancer Registry data.
Methods for auditing and enhancing completeness of ontologies
IIS-1931134 (NSF) | Licong Cui (PI)
05/01/2019 - 08/31/2021
The main goal of this project is to develop automated and scalable approaches for identifying potential incompleteness issues in biomedical ontologies as well as suggesting solutions to fix them.
An interface ontology for Alzheimer’s disease research
R21AG068994 (NIH) | Licong Cui (PI)
09/15/2020 - 05/31/2022
The main goal of this project is to develop a novel interface ontology for Alzheimer's disease (AD) research and web-based data exploration tools for managing, querying, and exploring AD data resources.
Biomedical terminology quality assurance for enhancing clinical queries over Electronic Health Records
R01LM013335 (NIH) | Licong Cui (PI)
08/01/2020 - 07/31/2022
The main goal of this project is to develop a general automatic change-suggestion framework to systematically address quality issues in biomedical terminologies and to quantitatively assess the terminology quality impact on clinical queries over EHRs for patient cohort identification.
Advancing cancer pharmacoepidemiology research through EHRS and informatics
U24CA194215 (NIH) | Hua Xu (PI)
09/01/2016 – 08/31/2021
The goal of this project is to integrate and extend previously developed tools to build an informatics infrastructure for electronic health records (EHR) data extraction, interpretation, management, and analysis, to advance cancer pharmacoepidemiology research.
Scalable methods for identity by descent
R01HG010086 (NIH) | Degui Zhi (PI)
06/01/2018 – 03/31/2022
In this project, we will develop and evaluate accurate and efficient methods and tools for detecting Identity-by-Descent (IBD) and local ancestry information in large genotyped cohorts, resources of increasing importance in the era of precision medicine.
Data science and informatics core for cancer research
RP170668 (CPRIT) | Wenjin Zheng (PI)
08/31/2017 – 08/30/2022
The goal of this project is to establish a data science and informatics infrastructure and translate cutting edge data science informatics software tools and algorithms developed at UTHealth for cancer research.
Metadata applications on informed content to facilitate biorepository data regulation and sharing
5U01HG009454 (NIH) | Cui Tao (PI)
09/28/2016 - 07/31/2020
This proposed study will focus on (1) developing a standard conforming metadata ontology to formally represent the informed consent domain; and (2) an automatic tool to semantically annotate informed consent documents to facilitate biorepository data regulation, sharing, and decision support.
Patient medical history representation, extraction, and inference from EHR data
R01LM011829 (NIH) | Cui Tao (PI)
09/01/2014 - 08/31/2020
This project will develop an ontology and semantic-based temporal relation modeling and reasoning tool for EHR.
Finding Combinatorial Drug Repositioning Therapy for Alzheimer's Disease and Related Dementias (supplement)
3R01AG066749-01S1 (NIH) | Cui Tao, Xiaoqian Jiang, Wenjin Zheng (MPI)
05/01/2020 – 03/31/2021
The goal of this project is to employ literature and machine learning to facilitate potential drug repurposing candidates for the elderly related to SARS-CoV-2 with a focus on CNS targets and CNS mechanisms.