AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

Bioinformatics (Oxford, England)
MOTIVATION: Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find i...

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

JAMA oncology
This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions.

Drug-drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths.

Bioinformatics (Oxford, England)
MOTIVATION: Adverse events resulting from drug-drug interactions (DDI) pose a serious health issue. The ability to automatically extract DDIs described in the biomedical literature could further efforts for ongoing pharmacovigilance. Most of neural n...

Biological Event Trigger Identification with Noise Contrastive Estimation.

IEEE/ACM transactions on computational biology and bioinformatics
Biological Event Extraction is an important task towards the goal of extracting biomedical knowledge from the scientific publications by capturing biomedical entities and their complex relations from the texts. As a crucial step in event extraction, ...

Using uncertainty to link and rank evidence from biomedical literature for model curation.

Bioinformatics (Oxford, England)
MOTIVATION: In recent years, there has been great progress in the field of automated curation of biomedical networks and models, aided by text mining methods that provide evidence from literature. Such methods must not only extract snippets of text t...

Identification of promising research directions using machine learning aided medical literature analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions. We presen...