Last update: February 21, 2022
CICADA: Clinical informatics and computational approaches for drug-repositioning
Project Period: 08/01/2021-07/31/2026
Agency: University of Pennsylvania/NIH PI: Cui Tao, Yong Chen (UPenn) (MPI)
Goal: The overarching goals of this project are to develop novel clinical informatics and computational approaches for drug repositioning of AD/ADRD. Specifically, the researchers will develop statistical methods and ontology technology to extract drug-repositioning signals from multidimensional data (e.g., pharmacy-linked genetic data and biobank data, historical trials, and EHR data). The proposed framework is novel because it integrates advanced statistical inference procedures with semantic technology for data-driven and reproducible drug repositioning for AD/ADRD.
Collaborative training of a new cadre of innovative cancer prevention researchers
Project Period: 2021 - 2026
Agency: CPRIT PI: Fernandez, Mullen, Swindell, Tao (MPI)
Goal: Training of pre-doctoral and post-doctoral research fellows.
AI-based conversational agent for facilitating education and communication about HPV vaccination in children and adolescents
Project Period: 3/1/2022-2/28/2026
Agency: CPRIT PI: Cui Tao
Goal: Development of an interactive conversational agent to enhance HPV vaccine awareness to decision makers (patients or parents of patients). The work involves a dialogue system that enriches a speech-enabled software agent to have prolonged, consistent, and lightweight counseling with a health consumer where the agent drives the conversation about the HPV vaccine. The results of the research team’s efforts will be a software agent that protects the privacy of the patient and is independent of third-party proprietary software vendors.
Using big data and deep learning on predicting HIV transmission risk in MSM population
Project Period: 09/01/2020 - 08/31/2022
Agency: NIH PI: Cui Tao, Kayo Fujimoto, John Schneider (MPI)
Goal: 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
Project Period: 02/01/2017 - 01/31/2022
Agency: NIH PI: Cui Tao (PI), Yong Chen (MPI)
Goal: 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
Project Period: 12/01/2019- 11/30/2023
Agency: AHA PI: Cui Tao
Goal: 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
Project Period: 05/01/2021 - 04/30/2024
Agency: NIH PI: Hua Xu, Cui Tao, and Hongfang Liu (Mayo Clinic) (MPI)
Goal: 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
Project Period: 05/15/2020 - 04/30/2025
Agency: NIH PI: Licong Cui
Goal: 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.
Methods for auditing and enhancing completeness of ontologies
Project Period: 08/31/2021 - 08/31/2026
Agency: NIH PI: Licong Cui
Goal: 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
Project Period: 09/15/2020 - 05/31/2022
Agency: NIH PI: Licong Cui
Goal: 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
Project Period: 08/01/2020 - 07/31/2022
Agency: NIH PI: Licong Cui
Goal: 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.
CAREER: Advancing the Role of Ontologies for Data Science in Biomedicine
Project Period: 09/01/2021 - 08/31/2026
Agency: NSF PI: Licong Cui
Goal: The goal of this project is to advance the role of ontologies for data science in biomedicine and address critical barriers in semantic interoperability and ontology quality.
Informatics tools to improve the interpretability and interoperability of informed consent instruments
Project Period: 09/16/2020 - 09/15/2021
Agency: NIH PI: Cui Tao (PI), Amy Franklin (Co-I), Muhammad Amith (Co-I)
Goal: 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.
Metadata applications on informed content to facilitate biorepository data regulation and sharing
Project Period: 09/28/2016 - 07/31/2020
Agency: NIH PI: Cui Tao
Goal: 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
Project Period: 09/01/2014 - 08/31/2020
Agency: NIH PI: Cui Tao
Goal: This project will develop an ontology and semantic-based temporal relation modeling and reasoning tool for EHR.
An ontology-driven faceted query engine for the Kentucky Cancer Registry
Project Period: 06/06/2018 - 07/31/2021
Agency: NIH PI: Licong Cui & GQ Zhang (MPI)
Goal: 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.