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- research-articleMarch 2023
Understanding common key indicators of successful and unsuccessful cancer drug trials using a contrast mining framework on ClinicalTrials.gov
Journal of Biomedical Informatics (JOBI), Volume 139, Issue Chttps://doi.org/10.1016/j.jbi.2023.104321Graphical abstractDisplay Omitted
Highlights- Clinical trial developers can learn insights from successful trials and avoid mistakes from unsuccessful trials from prior cases.
- Common characteristics from successful trials could be used to recommend cases that are similar to a new ...
Clinical trials are essential to the process of new drug development. As clinical trials involve significant investments of time and money, it is crucial for trial designers to carefully investigate trial settings prior to designing a trial. ...
- research-articleJanuary 2022
RHPTree—Risk Hierarchical Pattern Tree for Scalable Long Pattern Mining
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 16, Issue 4Article No.: 63, Pages 1–33https://doi.org/10.1145/3488380Risk patterns are crucial in biomedical research and have served as an important factor in precision health and disease prevention. Despite recent development in parallel and high-performance computing, existing risk pattern mining methods still struggle ...
- research-articleJune 2021
Explainable artificial intelligence in high-throughput drug repositioning for subgroup stratifications with interventionable potential
- Zainab Al-Taie,
- Danlu Liu,
- Jonathan B Mitchem,
- Christos Papageorgiou,
- Jussuf T. Kaifi,
- Wesley C. Warren,
- Chi-Ren Shyu
Journal of Biomedical Informatics (JOBI), Volume 118, Issue Chttps://doi.org/10.1016/j.jbi.2021.103792Graphical abstractDisplay Omitted
Highlights- Patient stratification is an essential part of precision medicine implementation.
Enabling precision medicine requires developing robust patient stratification methods as well as drugs tailored to homogeneous subgroups of patients from a heterogeneous population. Developing de novo drugs is expensive and time ...
