{"doi":"10.1101/2024.12.10.24318800","title":"Simulate Scientific Reasoning with Multiple Large Language Models: An Application to Alzheimer’s Disease Combinatorial Therapy","abstract":"Motivation: This study aims to develop an AI-driven framework that leverages large language models (LLMs) to simulate scientific reasoning and peer review to predict efficacious combinatorial therapy when data-driven prediction is infeasible. Results: Our proposed framework achieved a significantly higher accuracy (0.74) than traditional knowledge-based prediction (0.52). An ablation study highlighted the importance of high quality few-shot examples, external knowledge integration, self-consistency, and review within the framework. The external validation with private experimental data yielded an accuracy of 0.82, further confirming the framework's ability to generate high-quality hypotheses in biological inference tasks. Our framework offers an automated knowledge-driven hypothesis generation approach when data-driven prediction is not a viable option. Availability and implementation: Our source code and data are available at https://github.com/QidiXu96/Coated-LLM.","journal":"medRxiv","year":2024,"id":489390,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9542,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1334714,"name":"Xiaozhong Liu","orcid":"0000-0003-3477-8323","position":1,"is_corresponding":false},{"id":66208,"name":"Xiaoqian Jiang","orcid":"0000-0001-9933-2205","position":2,"is_corresponding":false},{"id":856330,"name":"Yejin Kim","orcid":"0000-0003-3900-6015","position":3,"is_corresponding":false},{"id":1256357,"name":"Qidi Xu","orcid":"0009-0006-6230-2719","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":null,"created_at":"2026-07-19T02:08:28.548530Z","pmid":"39711724","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}