A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Pierre Singer, Eyal Robinson, Orit Raphaeli
This review describes how AI tools, including deep learning and machine learning, can enhance clinical nutrition through improved screening, assessment, and prediction of outcomes, while addressing ethical considerations.
Stefano Mensa, Emre Sahin, Francesco Tacchino, et al.
Proposes a quantum-classical framework for ligand-based virtual screening that heuristically demonstrates prospective quantum advantage on real-world drug discovery datasets.
Anastasiia Sadybekov, Vsevolod Katritch
Reviews recent advances in computational drug discovery, emphasizing deep learning and virtual screening of gigascale chemical libraries.
F. J. Bolaños, Angelo A. Salatino, Francesco Osborne, et al.
This paper reviews AI techniques for semi-automating systematic literature reviews, focusing on screening and extraction phases.
Eva McCord, Ernest Pedapati, Zag ElSayed
A HIPAA-compliant, AI-augmented LIMS architecture using finite-state workflow models and automated QC pre-screening to optimize clinical assay workflows.