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A Machine Learning Approach Predicts Tissue-Specific Drug Adverse Events

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.279.15.1200openalex-snapshot

Incidence of Adverse Drug Reactions in Hospitalized Patients

inferredcites →https://doi.org/10.1007/s00520-012-1459-yopenalex-snapshot

Emergency department visits for symptoms experienced by oncology patients: a systematic review

inferredcites →https://doi.org/10.1007/s40264-016-0491-0openalex-snapshot

Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts

inferredcites →https://doi.org/10.1016/j.ddtec.2004.11.007openalex-snapshot

Lead- and drug-like compounds: the rule-of-five revolution

inferredcites →https://doi.org/10.1016/j.jmgm.2009.10.001openalex-snapshot

PubChem BioAssays as a data source for predictive models

inferredcites →https://doi.org/10.1021/acs.jcim.5b00238openalex-snapshot

Deep Learning for Drug-Induced Liver Injury

inferredcites →https://doi.org/10.1021/cc9800071openalex-snapshot

A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases

inferredcites →https://doi.org/10.1021/jm020017nopenalex-snapshot

Molecular Properties That Influence the Oral Bioavailability of Drug Candidates

inferredcites →https://doi.org/10.1038/477526aopenalex-snapshot

Translational research: 4 ways to fix the clinical trial

inferredcites →https://doi.org/10.1038/msb.2009.98openalex-snapshot

A side effect resource to capture phenotypic effects of drugs

inferredcites →https://doi.org/10.1038/nbt.2786openalex-snapshot

Clinical development success rates for investigational drugs

inferredcites →https://doi.org/10.1038/nchem.1243openalex-snapshot

Quantifying the chemical beauty of drugs

inferredcites →https://doi.org/10.1038/nrc1951openalex-snapshot

The NCI60 human tumour cell line anticancer drug screen

inferredcites →https://doi.org/10.1093/nar/gkn698openalex-snapshot

ConsensusPathDB—a database for integrating human functional interaction networks

inferredcites →https://doi.org/10.1093/nar/gkv1192openalex-snapshot

WITHDRAWN—a resource for withdrawn and discontinued drugs

inferredcites →https://doi.org/10.1126/science.1132939openalex-snapshot

The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease

inferredcites →https://doi.org/10.1126/science.1262110openalex-snapshot

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

inferredcites →https://doi.org/10.1158/1538-7445.am2016-3916openalex-snapshot

Abstract 3916: A “moneyball” approach to predicting clinical trial toxicity events

inferredcites →https://doi.org/10.2165/00019053-199915050-00003openalex-snapshot

Counting the Costs of Drug-Related Adverse Events

inferredcites →https://doi.org/10.4103/0976-500x.120957openalex-snapshot

Clinical and economic burden of adverse drug reactions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/wcms.1408openalex-snapshot

Formatting biological big data for modern machine learning in drug discovery

inferred← citeshttps://doi.org/10.1016/j.tips.2019.06.001openalex-snapshot

The Missing Pieces of Artificial Intelligence in Medicine

inferred← citeshttps://doi.org/10.1080/09205063.2026.2675360openalex-snapshot

Machine learning in tissue engineering: a comprehensive review of applications, challenges, and prospects

inferred← citeshttps://doi.org/10.1089/ten.teb.2024.0022openalex-snapshot

Application of Artificial Intelligence in Tissue Engineering

inferred← citeshttps://doi.org/10.1101/576017openalex-snapshot

Multi-task learning predicts drug combination synergy in cells and in the clinic

inferred← citeshttps://doi.org/10.1186/s13036-019-0185-0openalex-snapshot

Cardiac tissue engineering: state-of-the-art methods and outlook

inferred← citeshttps://doi.org/10.1371/journal.pcbi.1008098openalex-snapshot

A machine learning and network framework to discover new indications for small molecules

inferred← citeshttps://doi.org/10.5599/admet.2772openalex-snapshot

Leveraging machine learning models in evaluating ADMET properties for drug discovery and development

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