activity
20122022
most citedApplications of artificial intelligence in drug development using real-world data

101 citations · 229 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DB2022★ 72 cited

Ontology Development Kit: a toolkit for building, maintaining, and standardising biomedical ontologies

Nicolas Matentzoglu, Damien Goutte-Gattat, Shawn Zheng Kai Tan +24

Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking, and dep…

cs.CL2021★ 38 cited

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…

cs.CY2021★ 101 cited

Applications of artificial intelligence in drug development using real-world data

Zhaoyi Chen, Xiong Liu, William Hogan +2

The US Food and Drug Administration (FDA) has been actively promoting the use of real-world data (RWD) in drug development. RWD can generate important real-world evidence reflectin…

q-bio.QM2019★ 10 cited

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…

stat.AP2019★ 7 cited

Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network: A Colorectal Cancer Clinical Trial Case Study

Qian Li, Zhe He, Yi Guo +5

Existing trials had not taken enough consideration of their population representativeness, which can lower the effectiveness when the treatment is applied in real-world clinical pr…

stat.AP2012★ 1 cited

Bayesian Biosurveillance of Disease Outbreaks

Gregory F. Cooper, Denver Dash, John Levander +3

Early, reliable detection of disease outbreaks is a critical problem today. This paper reports an investigation of the use of causal Bayesian networks to model spatio-temporal patt…