AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia.
Aliaksandra SikirzhytskayaIlya TyaginS Scott SuttonMichael D WyattIlya SafroMichael S ShtutmanPublished in: bioRxiv : the preprint server for biology (2024)
This manuscript outlines our project involving the application of AGATHA, an AI-based literature mining tool, to discover drugs with the potential for repurposing in the context of neurocognitive disorders. The primary objective is to identify connections between approved medications and specific health conditions through advanced statistical analysis, including techniques like Partial Least Squares Discriminant Analysis (PLSDA) and unsupervised clustering. The methodology involves grouping scientific terms related to different health conditions and genes, followed by building discrimination models to extract lists of disease-specific genes. These genes are then analyzed through pathway analysis to select candidates for drug repurposing.
Keyphrases
- healthcare
- public health
- systematic review
- genome wide
- artificial intelligence
- mental health
- bioinformatics analysis
- machine learning
- mild cognitive impairment
- gene expression
- drug induced
- health information
- dna methylation
- oxidative stress
- human health
- single cell
- emergency department
- deep learning
- adverse drug
- transcription factor
- genome wide analysis
- rna seq
- social media