Health AI Central
Peer-Reviewed Publication
Bioinformatics2026;42(Supplement_1)July 1, 2026Journal Article

eGoT: enhanced graph-of-thoughts for multi-hop knowledge retrieval and hypothesis generation in biomedicine.

Nihar Sanda1, Benjamin M Gyori2,3, Vito Quaranta1,4, Auroop Ganguly1,5, Ayan Paul1,2
1The Institute for Experiential AI, Northeastern University, Boston, MA 02115, United States.
2Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, United States.
3Department of Bioengineering, Northeastern University, Boston, MA 02115, United States.
4Bouvé College of Health Sciences, Northeastern University, Boston, MA 02115, United States.
5Department of Civil and Mechanical Engineering, Northeastern University, Boston, MA 02115, United States.
PubMed PMC DOI PDF

Abstract

MOTIVATION: Research on biological mechanisms and disease processes is limited by fragmented findings across unstructured text in publications. Question answering and hypothesis generation that can reason across multiple sources can overcome this limitation. However, Large language models (LLMs) are prone to inaccuracies and lack clear provenance to primary evidence. Retrieval augmented generation…

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