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DeepBD workflow enhances genetic birth defect diagnosis

Researchers have developed DeepBD, a novel agentic workflow designed to improve the diagnosis of genetic birth defects. This system integrates LLM-assisted case structuring, a pretrained evidence engine, and specialist modules to refine variant prioritization. Tested on a cohort of 18,622 cases, DeepBD demonstrated strong performance in recall metrics, outperforming existing tools like Exomiser and DeepRare. AI

IMPACT This workflow could accelerate diagnostic timelines for rare genetic diseases, improving patient outcomes.

RANK_REASON Research paper detailing a new AI-driven workflow for a specific scientific domain.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

DeepBD workflow enhances genetic birth defect diagnosis

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Shiyu Li, Ziqi Yan, Zhihao Wu, Jielong Lu, Weiran Liao, Jiajun Yu, Genjie Li, Zeyu Chu, Jiajun Bu, Haishuai Wang ·

    DeepBD: A Grounded Agentic Workflow for Variant Prioritization and Diagnosis of Genetic Birth Defects

    arXiv:2606.24779v1 Announce Type: cross Abstract: Birth defects are a major cause of fetal loss, neonatal morbidity and long-term disability. In the subset with suspected genetic etiologies, exome and genome sequencing have moved many cases from variant detection to post-sequenci…

  2. arXiv cs.AI TIER_1 English(EN) · Haishuai Wang ·

    DeepBD: A Grounded Agentic Workflow for Variant Prioritization and Diagnosis of Genetic Birth Defects

    Birth defects are a major cause of fetal loss, neonatal morbidity and long-term disability. In the subset with suspected genetic etiologies, exome and genome sequencing have moved many cases from variant detection to post-sequencing interpretation: clinicians must rank patient-sp…