Dyport: dynamic importance-based biomedical hypothesis generation benchmarking technique

• Published in: BMC bioinformatics Vol. 25; no. 1; pp. 213 - 28
• Main Authors: Tyagin, Ilya, Safro, Ilya
• Format: Journal Article
• Language: English
• Published: England BioMed Central 13.06.2024; BMC
• Subjects: Algorithms; Artificial intelligence; Automation; Benchmarking; Benchmarking - methods; Benchmarks; Biomedical Research - methods; Computational Biology - methods; Data mining; Databases, Factual; Datasets; Hypotheses; Hypothesis Generation; Knowledge representation; Link Prediction; Literature-based Discovery; Machine Learning; Medical research; Natural Language Processing; R&D; Research & development; Semantics; Software; Source code; Subject specialists; Systems analysis; Literature-based Discovery; Benchmarking; Link Prediction; Hypothesis Generation; Natural Language Processing

Automated hypothesis generation (HG) focuses on uncovering hidden connections within the extensive information that is publicly available. This domain has become increasingly popular, thanks to modern machine learning algorithms. However, the automated evaluation of HG systems is still an open probl...