Comprehensive evaluation of deep and graph learning on drug–drug interactions prediction

X Lin, L Dai, Y Zhou, ZG Yu, W Zhang… - Briefings in …, 2023 - academic.oup.com
Recent advances and achievements of artificial intelligence (AI) as well as deep and graph
learning models have established their usefulness in biomedical applications, especially in …

Use of electronic health record data for drug safety signal identification: a scoping review

SE Davis, L Zabotka, RJ Desai, SV Wang, JC Maro… - Drug Safety, 2023 - Springer
Introduction Pharmacovigilance programs protect patient health and safety by identifying
adverse event signals through postmarketing surveillance of claims data and spontaneous …

Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension

P Wu, QP Feng, VE Kerchberger, SD Nelson… - Nature …, 2022 - nature.com
Discovering novel uses for existing drugs, through drug repurposing, can reduce the time,
costs, and risk of failure associated with new drug development. However, prioritizing drug …

MECDDI: clarified drug–drug interaction mechanism facilitating rational drug use and potential drug–drug interaction prediction

W Hu, W Zhang, Y Zhou, Y Luo, X Sun… - Journal of Chemical …, 2023 - ACS Publications
Drug–drug interactions (DDIs) are a major concern in clinical practice and have been
recognized as one of the key threats to public health. To address such a critical threat, many …

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

JA Pacheco, LV Rasmussen, K Wiley Jr, TN Person… - Scientific reports, 2023 - nature.com
Abstract The electronic Medical Records and Genomics (eMERGE) Network assessed the
feasibility of deploying portable phenotype rule-based algorithms with natural language …

SLCO1B1*5 Allele Is Associated With Atorvastatin Discontinuation and Adverse Muscle Symptoms in the Context of Routine Care

D Voora, J Baye, A McDermaid… - Clinical …, 2022 - Wiley Online Library
The SLCO1B1 genotype is known to influence patient adherence to statin therapy, in part by
increasing the risk for statin‐associated musculoskeletal symptoms (SAMSs). The …

Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions

WQ Wei, R Rowley, A Wood, J MacArthur… - Journal of the …, 2024 - academic.oup.com
Introduction Phenotyping algorithms enable the interpretation of complex health data and
definition of clinically relevant phenotypes; they have become crucial in biomedical …

Adaptive regularized multiattribute fuzzy distance learning for predicting adverse drug–drug interaction

J Zhu, Y Liu, Y Zhang, Z Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Adverse drug–drug interaction (ADDI) causes harmful injuries and accidental deaths in
patients, posing as a significant life-threatening issue in public health. Early prediction of …

Novel analysis methods to mine immune-mediated phenotypes and find genetic variation within the electronic health record (roadmap for phenotype to genotype …

MS Krantz, VE Kerchberger, WQ Wei - The Journal of Allergy and Clinical …, 2022 - Elsevier
The field of immunogenomics has the opportunity for accelerated genetic discovery aided by
the maturation of electronic health records (EHRs) linked to DNA biobanks. Novel analysis …

Systematic Estimation of Treatment Effect on Hospitalization Risk as a Drug Repurposing Screening Method

C Georgantas, J Banus, R Hullin… - PACIFIC SYMPOSIUM …, 2023 - World Scientific
Drug repurposing (DR) intends to identify new uses for approved medications outside their
original indication. Computational methods for finding DR candidates usually rely on prior …