哈佛医学院研究人员开发了50%更有效的人工智能模型TxGNN,以识别17 000种罕见疾病的药物候选者。 Harvard Medical School researchers developed a 50% more effective AI model, TxGNN, to identify drug candidates for 17,000 rare diseases.

哈佛医学院研究人员创建了一个名为TxGNN的AI模型,用于识别17,000多种罕见疾病的药物候选者,其中许多疾病缺乏治疗。 Harvard Medical School researchers have created an AI model called TxGNN to identify drug candidates for over 17,000 rare diseases, many lacking treatments. 这一创新工具分析现有药物,预测潜在的副作用和反作用,比目前模式有效50%。 This innovative tool analyzes existing medications, predicting potential side effects and contraindications, and is 50% more effective than current models. 该方案免费提供,旨在协助临床科学家开发新的疗法,并解决在服务不足条件下的保健差距问题。 Freely available, it aims to assist clinician-scientists in developing new therapies and addressing health disparities in underserved conditions.