BioResearcher: Scenario-Guided Multi-Agent for Translational Medicine

• URL: http://arxiv.org/abs/2605.05985v1
• Date: Thu, 07 May 2026 10:33:43 GMT
• Title: BioResearcher: Scenario-Guided Multi-Agent for Translational Medicine
• Abstract summary: Ingenix BioResearcher is a scenario-guided multi-agent system that maps queries to versioned research playbooks.<n>We evaluate BioResearcher across unit-level capabilities, open-ended biomedical reasoning, and end-to-end clinical discovery.
• Score: 1.497336135403194
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Translational medicine turns underspecified development goals into evidence synthesis that must combine literature, trials, patents, and quantitative multi-omics analysis while preserving identifiers, uncertainty, and retrievable provenance. General-purpose foundation models and off-the-shelf tool-augmented or multi-agent systems are not built for this: they tend to produce single-shot answers or run open-endedly, and fall short on the auditable, scenario-specific workflows that heterogeneous biomedical sources demand. This paper introduces Ingenix BioResearcher, a scenario-guided multi-agent system that maps queries to versioned research playbooks, delegates to specialized subagents over 30+ tools and machine-learning endpoints, mixes structured database access with sandboxed code for genome-scale analyses, and applies claim-level multi-model reconciliation before editorial assembly. We evaluate BioResearcher across unit-level capabilities, open-ended biomedical reasoning, and end-to-end clinical discovery. It leads evaluated baselines on 109 single-step tests (83.49% pass rate; 0.892 average score), achieves strong biomedical benchmark performance (89.33% on BixBench-Verified-50 and the top 0.758 mean score on BaisBench Scientific Discovery), and leads on a 30-query clinical end-to-end benchmark with the highest positive hit rate (74.7% $\pm$ 3.3%) and negative clear rate (96.8% $\pm$ 0.2%). These results show broad, competitive performance across unit-level, open-ended, and end-to-end clinical evaluations.

Related papers

• FrontierChallenge: Evaluating Scientific Workflow Completion [59.601983661596286]
  We introduce FrontierChallenge, a cross-domain benchmark comprising 300 end-to-end scientific deliverables.<n>We release and evaluate 97 of these tasks, spanning quantum chemistry, molecular dynamics, materials characterization, analytical chemistry, life science, and electrochemistry/environment.<n>We find that neither high partial scores nor confident claims of completion reliably indicate that a scientific task has been fully delivered.
  arXiv  Detail & Related papers  (2026-08-25T16:50:58Z)
• Generating Biomedical Fact-Checking Reports with RL-Enhanced Agentic Search [7.057804937676404]
  BioCheck Agent generates structured biomedical fact-checking reports with agentic search.<n>Agent searches high-quality scientific literature in PubMed.<n>It achieves a 3.7% higher evidence quality score and a 19.63% lower evidence hallucination rate.
  arXiv  Detail & Related papers  (2026-08-24T20:25:38Z)
• Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting [59.709162055944915]
  ThyroidXAgent is an agentic AI system that coordinates specialized diagnostic tools and stores their outputs as an auditable case-level evidence record.<n>It was evaluated on 28,458 non-overlapping test cases, including 8,721 cases from 35 centres in the private NHC-MISD-TUS cohort.<n>It achieved a mean Dice score of 87.21 percent for segmentation and a mean AUROC of 0.9466 for benign-malignant classification.
  arXiv  Detail & Related papers  (2026-08-12T21:02:59Z)
• BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents [35.04967801827194]
  We release BioMedArena, an open-source toolkit for evaluating deep-research agents.<n>BioMedArena decouples six layers of biomedical agent evaluation.<n>It exposes 147 biomedical benchmarks and 75 biomedical tools across 9 functional families.
  arXiv  Detail & Related papers  (2026-05-07T12:57:18Z)
• Health System Scale Semantic Search Across Unstructured Clinical Notes [1.599023522858371]
  We deploy a semantic search system at a large children's hospital indexing 166 million clinical notes from 1.68 million patients.<n>The system delivers sub-latency query latency (median 237 ms single-user, 451 ms 20-usertoken) with monthly costs of approximately USD 4,000.
  arXiv  Detail & Related papers  (2026-04-28T13:09:48Z)
• BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature [53.894504720119805]
  We introduce BioMiner, a multi-modal extraction framework for bioactivity data extraction.<n>Within BioMiner, bioactivity semantics are inferred through direct reasoning, while chemical structures are resolved via a chemical-structure-grounded visual semantic reasoning paradigm.<n>For rigorous evaluation and method development, we establish a benchmark comprising 16,457 bioactivity entries curated from 500 publications.
  arXiv  Detail & Related papers  (2026-04-23T10:11:56Z)
• Eligibility-Aware Evidence Synthesis: An Agentic Framework for Clinical Trial Meta-Analysis [49.83108591873481]
  EligMeta is an agentic framework that integrates automated trial discovery with eligibility-aware meta-analysis.<n>The framework structures eligibility criteria and computes similarity-based study weights reflecting population alignment between target trials.
  arXiv  Detail & Related papers  (2026-04-03T03:18:50Z)
• Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment [56.62016795093786]
  Cerebra is an interactive multi-agent AI team that coordinates specialized agents for EHR, clinical notes, and medical imaging analysis.<n>It supports privacy-preserving deployment by operating on structured representations and remains robust when modalities are incomplete.<n>Cerebra significantly improved expert performance, increasing accuracy by 17.5 percentage points in prospective dementia risk estimation.
  arXiv  Detail & Related papers  (2026-03-23T05:46:45Z)
• QuarkMedBench: A Real-World Scenario Driven Benchmark for Evaluating Large Language Models [8.050059911826338]
  Large Language Models (LLMs) excel on standardized medical exams, but high scores often fail to translate to high-quality responses for real-world medical queries.<n>We introduce QuarkMedBench, an ecologically valid benchmark tailored for real-world medical LLM assessment.
  arXiv  Detail & Related papers  (2026-03-14T01:51:43Z)
• TriAgent: Automated Biomarker Discovery with Deep Research Grounding for Triage in Acute Care by LLM-Based Multi-Agent Collaboration [3.0416960239499358]
  Emergency departments worldwide face rising patient volumes, workforce shortages, and variability in triage decisions.<n>To address this challenge, we introduce TriAgent, a large language model (LLM)-based multi-agent framework.<n>TriAgent couples automated biomarker discovery with deep research for literature-grounded validation and novelty assessment.
  arXiv  Detail & Related papers  (2025-10-17T12:26:29Z)
• BioMedSearch: A Multi-Source Biomedical Retrieval Framework Based on LLMs [8.505934574757587]
  We present BioMedSearch, a biomedical information retrieval framework based on large language models (LLMs)<n>The method integrates literature retrieval, protein database and web search access to support accurate and efficient handling of complex biomedical queries.<n>To evaluate the accuracy of question answering, we constructed a multi-level dataset, BioMedMCQs, consisting of 3,000 questions.
  arXiv  Detail & Related papers  (2025-10-15T13:01:31Z)
• An Agentic System for Rare Disease Diagnosis with Traceable Reasoning [69.46279475491164]
  We introduce DeepRare, the first rare disease diagnosis agentic system powered by a large language model (LLM)<n>DeepRare generates ranked diagnostic hypotheses for rare diseases, each accompanied by a transparent chain of reasoning.<n>The system demonstrates exceptional diagnostic performance among 2,919 diseases, achieving 100% accuracy for 1013 diseases.
  arXiv  Detail & Related papers  (2025-06-25T13:42:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.