Model Medicine is the science of understanding, diagnosing, treating, and preventing disorders in AI models, grounded in the principle that AI models -- like biological organisms -- have internal structures, dynamic processes, heritable traits, observable symptoms, classifiable conditions, and treatable states. This paper introduces Model Medicine as a research program, bridging the gap between current AI interpretability research (anatomical observation) and the systematic clinical practice that complex AI systems increasingly require. We present five contributions: (1) a discipline taxonomy organizing 15 subdisciplines across four divisions -- Basic Model Sciences, Clinical Model Sciences, Model Public Health, and Model Architectural Medicine; (2) the Four Shell Model (v3.3), a behavioral genetics framework empirically grounded in 720 agents and 24,923 decisions from the Agora-12 program, explaining how model behavior emerges from Core--Shell interaction; (3) Neural MRI (Model Resonance Imaging), a working open-source diagnostic tool mapping five medical neuroimaging modalities to AI interpretability techniques, validated through four clinical cases demonstrating imaging, comparison, localization, and predictive capability; (4) a five-layer diagnostic framework for comprehensive model assessment; and (5) clinical model sciences including the Model Temperament Index for behavioral profiling, Model Semiology for symptom description, and M-CARE for standardized case reporting. We additionally propose the Layered Core Hypothesis -- a biologically-inspired three-layer parameter architecture -- and a therapeutic framework connecting diagnosis to treatment.

翻译：模型医学是一门基于以下原理的科学：理解、诊断、治疗和预防AI模型的失调状态，其原理在于AI模型——如同生物有机体——具有内部结构、动态过程、可遗传特征、可观察症状、可分类状况以及可治疗状态。本文引入模型医学作为一个研究计划，旨在弥合当前AI可解释性研究（解剖学观察）与日益复杂的AI系统所需的系统性临床实践之间的差距。我们提出了五项贡献：（1）一个学科分类法，将15个子学科组织在四个分支下——基础模型科学、临床模型科学、模型公共卫生和模型架构医学；（2）四层外壳模型（v3.3），这是一个行为遗传学框架，其经验基础来自Agora-12项目的720个智能体和24,923个决策，解释了模型行为如何从核心-外壳交互中涌现；（3）神经MRI（模型共振成像），一个可工作的开源诊断工具，将五种医学神经成像模式映射到AI可解释性技术，并通过四个临床案例验证，展示了成像、比较、定位和预测能力；（4）一个用于全面模型评估的五层诊断框架；以及（5）临床模型科学，包括用于行为分析的模型气质指数、用于症状描述的模型症状学，以及用于标准化病例报告的M-CARE。我们还提出了分层核心假说——一个受生物学启发的三层参数架构——以及一个连接诊断与治疗的治疗框架。