报告人：许燕勋

报告题目：HIV-AICare: A Domain Knowledge-guided AI Tool for Optimizing Antiretroviral Therapy in People with HIV

时间：2025年12月12日 10:00-12:00

地点：数学楼2-3会议室

报告摘要：

Despite the success of antiretroviral therapy (ART) in achieving viral suppression in people with HIV (PWH), numerous ART-related adverse effects have been reported. Effective HIV management should prioritize viral suppression while simultaneously minimizing adverse effects, with regimens tailored to the specific characteristics of each individual. However, there is a lack of individualized approaches that leverage real-world evidence to assist with ART selection in clinical practice, particularly for treatment-experienced PWH. To address this, we developed HIV-AICare, a data-driven artificial intelligence (AI) tool for personalized ART selection. Leveraging reinforcement learning and clinical guidelines, HIV-AICare streamlines the complex process of selecting ART regimens, optimizing both treatment efficacy and long-term patient outcomes. Applied to the MACS/WIHS Combined Cohort Study data, HIV-AICare effectively navigates HIV treatment complexities uncovers patterns in ART-related adverse effects and provides clinicians with actionable insights.  Its recommendations align with current clinical practice, offering tailored, guideline-compliant treatment options, highlighting the potential of a data-driven and domain knowledge-guided approach to enhance clinical decision-making.

报告人简介：

许燕勋教授，现任美国约翰斯霍普金斯制服做爱 应用数学与统计系终身教职教授(博士生导师), 并荣膺Joseph &Suzanne Jenniches冠名教授。她长期致力于贝叶斯统计理论与人工智能交叉研究，在强化学习，高维数据分析，非参数统计及不确定性量化等领域取得重要突破。其创新性统计机器学习方法已成功应用于智能医疗健康多个核心领域，包括精准医疗(临床试验设计，癌症基因组学，个性化治疗)，疾病早期诊断(阿尔茨海默病预测模型)，以及电子健康记录智能分析。曾获ISBA世界大会 Mitchel Prize等重要学术奖项。目前担任国际贝叶斯分析学会(ISBA)执行委员会财务主管，并任《Bayesian Analysis》主编及多个统计学期刊副主编。作为独立PI，其研究持续获得美国国家科学基金会(NSF)，国立卫生研究院(NIH)及工业界资助，在人工智能驱动的大健康研究领城形成了"基础理论-算法开发-临床转化"的完整创新链，推动了人工智能在医疗健康领域的科学化应用。

邀请人：姜丹丹教授