A Locally Executable AI System for Improving Preoperative Patient Communication: A Multi-Domain Clinical Evaluation
Nagasaki University Graduate School of Biomedical Sciences（长崎大学生物医学科学研究科）；Boston Medical Sciences, Inc.（波士顿医学科学公司）；Showa Medical University Koto Toyosu Hospital（昭和医科大学江东丰洲医院）
32 pages, 4 figures, 10 tables 32 pages, 4 figures, 10 tables. This paper is currently under review at ACM Transactions on Computing for Healthcare. Reproducibility resources: http://github.com/motokinaru/LENOHA-medical-dialogue
Patients awaiting invasive procedures often have unanswered pre-procedural questions; however, time-pressured workflows and privacy constraints limit personalized counseling. We present LENOHA (Low Energy, No Hallucination, Leave No One Behind Architecture), a safety-first, local-first system that routes inputs with a high-precision sentence-transformer classifier and returns verbatim answers from a clinician-curated FAQ for clinical queries, eliminating free-text generation in the clinical path. We evaluated two domains (tooth extraction and gastroscopy) using expert-reviewed validation sets (n=400/domain) for thresholding and independent test sets (n=200/domain). Among the four encoders, E5-large-instruct (560M) achieved an overall accuracy of 0.983 (95% CI 0.964-0.991), AUC 0.996, and seven total errors, which were statistically indistinguishable from GPT-4o on this task; Gemini made no errors on this test set. Energy logging shows that the non-generative clinical path consumes ~1.0 mWh per input versus ~168 mWh per small-talk reply from a local 8B SLM, a ~170x difference, while maintaining ~0.10 s latency on a single on-prem GPU. These results indicate that near-frontier discrimination and generation-induced errors are structurally avoided in the clinical path by returning vetted FAQ answers verbatim, supporting privacy, sustainability, and equitable deployment in bandwidth-limited environments.
Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural Network
Seoul National University College of Medicine（首尔大学医学院）；SMG-SNU Boramae Medical Center（首尔市立大学首尔大学Borame医疗中心）；Hanyang University（汉阳大学）；Hankuk University of Foreign Studies（韩国外国语大学）；Canon Medical Systems Korea（佳能医疗系统韩国公司）；Yonsei University College of Medicine（延世大学医学院）
Treatment-wise Glioblastoma Survival Inference with Multi-parametric Preoperative MRI
Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School（戈登医学影像中心，麻省总医院和哈佛医学院）；University of Southern California（南加州大学）；Yale University（耶鲁大学）
Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma
European Institute of Oncology, IEO, IRCCS（欧洲肿瘤研究所）；Politecnico di Milano（米兰理工大学）；INESC TEC, Faculty of Engineering, University of Porto（波尔图大学工程学院INESC TEC）；University of Cambridge（剑桥大学）；Cancer Research UK Cambridge Centre（英国癌症研究中心剑桥中心）；Cancer Research UK Cambridge Institute（英国癌症研究中心剑桥研究所）；Cambridge University Hospitals NHS Foundation Trust（剑桥大学医院NHS基金会信托）；Mayo Clinic（梅奥诊所）；Early Cancer Institute, University of Cambridge（剑桥大学早期癌症研究所）；Danube Private University（多瑙私立大学）；University of Milan（米兰大学）；Università Cattolica del Sacro Cuore（圣心天主教大学）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）
A Vision-Language Foundation Model for Precise and Comprehensive Brain Tumor Diagnosis from Preoperative Multimodal Data
The University of Hong Kong（香港大学）；Xiangya Hospital, Central South University（中南大学湘雅医院）；Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City)（中南大学湘雅医学院常德医院（常德市第一人民医院））；Stanford University（斯坦福大学）；The Second Affiliated Hospital, Hengyang Medical School, University of South China（南华大学衡阳医学院附属第二医院）；The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University（南昌大学江西医学院第二附属医院）；The First Affiliated Hospital, Jiangxi Medical College, Nanchang University（南昌大学江西医学院第一附属医院）；Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College（南昌医学院第一附属医院江西省人民医院）；The Affiliated Children’s Hospital of Xiangya School of Medicine, Hunan Children’s Hospital（湖南儿童医院湘雅医学院附属儿童医院）；Shenzhen Second People’s Hospital（深圳市第二人民医院）；First Hospital of Lanzhou University（兰州大学第一医院）；The Third Xiangya Hospital, Central South University（中南大学湘雅三医院）；Tongji Hospital, School of Medicine, Tongji University（同济大学附属同济医院）；Chongqing Traditional Chinese Medicine Hospital（重庆市中医院）；Basis International School Park Lane Harbour（柏朗思观澜湖国际学校）；University of California, Santa Cruz（加州大学圣克鲁兹分校）；National Clinical Research Center of Geriatric Disorders, Xiangya Hospital, Central South University（中南大学湘雅医院国家老年疾病临床医学研究中心）
MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoning
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Albert Einstein College of Medicine（爱因斯坦医学院）
Multiscale Cross-Modal Mapping of Molecular, Pathologic, and Radiologic Phenotypes in Lipid-Deficient Clear Cell Renal CellCarcinoma
Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University（江苏省人工智能影像与介入放射学 state laboratory 育成中心，放射科，中大医院，东南大学）；Department of Mechanical and Aerospace Engineering, Princeton University（机械与航空航天工程系，普林斯顿大学）；School of Automation, Southeast University（自动化学院，东南大学）；Department of Biomedical Engineering, Columbia University（生物医学工程系，哥伦比亚大学）；Automation and Electrical Engineering College, Lanzhou University of Technology（自动化与电气工程学院，兰州理工大学）；The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China（中国科学技术大学附属第一医院，生命科学与医学学院，中国科学技术大学）；Lianyungang First People’s Hospital（连云港第一人民医院）；School of Robotics and Automation, Suzhou Campus, Nanjing University（机器人与自动化学院，南京大学苏智校区）
PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets
Seoul National University（首尔大学）；Korea University Guro Hospital（高丽大学九老医院）；Seoul National University College of Medicine（首尔大学医学院）；Seoul National University Bundang Hospital（首尔大学盆唐医院）；Hankuk University of Foreign Studies（韩国外国语大学）
CPGPrompt: Translating Clinical Guidelines into LLM-Executable Decision Support
Information Science (Health Tech), Cornell Tech, New York, NY, USA（信息科学（健康科技），康奈尔科技，纽约，纽约州）；Systems Engineering, Cornell University, Ithaca, NY, USA（系统工程，康奈尔大学，伊萨卡，纽约州）；Population Health Sciences, Weill Cornell Medicine, New York, NY, USA（人口健康科学，韦尔医学院，纽约，纽约州）；Computer and Information Science, Cornell University, Ithaca, NY, USA（计算机与信息科学，康奈尔大学，伊萨卡，纽约州）；Department of Biomedical Informatics, Columbia University, New York, NY, USA（生物医学信息学系，哥伦比亚大学，纽约，纽约州）；Department of Medicine, Weill Cornell Medicine, New York, NY, USA（医学系，韦尔医学院，纽约，纽约州）；Department of Health Information Management, University of Pittsburgh, Pittsburgh, PA, USA（健康信息管理系，匹兹堡大学，匹兹堡，宾夕法尼亚州）；Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA（临床与转化科学研究所，匹兹堡大学，匹兹堡，宾夕法尼亚州）；Department of Neurology, UT Southwestern Medical Center, Dallas, TX, USA（神经病学系，德克萨斯西南医学中心，达拉斯，德克萨斯州）；Peter O’Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA（彼得·奥·donnell Jr.脑研究所，德克萨斯西南医学中心，达拉斯，德克萨斯州）；Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, USA（临床信息学中心，德克萨斯西南医学中心，达拉斯，美国）；Institute of Artificial Intelligence for Digital Health, Weill Cornell Medicine, New York, NY USA（数字健康人工智能研究所，韦尔医学院，纽约，纽约州）
Machine Learning Based Prediction of Surgical Outcomes in Chronic Rhinosinusitis from Clinical Data
Purdue University（普渡大学）；Idaho National Laboratory（爱达荷国家实验室）；Indiana University Indianapolis（印第安纳大学印第安纳波利斯分校）；Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina（斯克内尔医学院耳鼻喉科与头颈外科部门）；Department of Otolaryngology-Head and Neck Surgery, University of California, Los Angeles（加州大学洛杉矶分校耳鼻喉科与头颈外科部门）；Department of Otolaryngology-Head and Neck Surgery, University of Utah（犹他大学耳鼻喉科与头颈外科部门）；Department of Otolaryngology-Head and Neck Surgery, Oregon Health Sciences University（俄勒冈健康科学大学耳鼻喉科与头颈外科部门）；Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine（印第安纳大学医学院耳鼻喉科与头颈外科部门）
Automated surgical planning with nnU-Net: delineation of the anatomy in hepatobiliary phase MRI
The Netherlands Cancer Institute – Antoni van Leeuwenhoek（荷兰癌症研究所 – 安东尼·范·列文虎克）；National Center for Tumor Diseases (NCT), NCT/UCC Dresden（国家肿瘤疾病中心（NCT），NCT/UCC 德累斯顿）；DKFZ（德国癌症研究中心）；Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology（德累斯顿工业大学医学院及卡尔·古斯塔夫·卡鲁斯大学医院）；The Centre for Tactile Internet with Human-in-the-Loop (CeTI), TUD Dresden University of Technology（德累斯顿工业大学触觉互联网与人机协同中心）；University of Twente（特文特大学）
