Hugging Face Trending Papers

FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization

Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk. These challenges are particularly pronounced in multi-day assays such as Luminex-based quantification of Fragile X Messenger Ribonucleoprotein (FMRP), where HIPAA-compliant data governance, deterministic workflow progression, and coordinated communication across laboratory and clinical teams are required.

arXiv AI
Jul 23

FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization

arXiv:2607. 20382v1 Announce Type: cross Abstract: Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk.

By Eva McCord, Ernest Pedapati, Zag ElSayed
arXiv AI
Aug 11

From Single Chatbots to Governed Agent Ecosystems: An Agentic AI Pattern Catalogue and Orchestration Framework for Mission-Critical Hospital Information Management Systems

arXiv:2608. 07627v1 Announce Type: new Abstract: Hospitals are racing to embed AI, while coping with the surge in adaptation of the technology in other industries, into the triage management, documentation, scheduling, and revenue-cycle workflows, yet most deployments remain as fragmented pilots that stall at the edge of production, exposing patients and institutions to operational fragility, ungoverned risk, and mounting technical debt.

By Manideep Dhar, Ritwik Singh, Sharat Chandra Kumar Manikonda
arXiv AI
Jul 14

NVAITC AI Scientist: A Governed End-to-End Research System -- A Hypertension GWAS Case Study

arXiv:2607. 11084v1 Announce Type: new Abstract: Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond isolated model inference, code generation, or statistical analysis.

By Eddie Huang (NVIDIA AI Technology Center, NVIDIA Corporation), Ken Liao (NVIDIA AI Technology Center, NVIDIA Corporation), Iven Fu (NVIDIA AI Technology Center, NVIDIA Corporation), Yang-Hsien Lin (NVIDIA AI Technology Center, NVIDIA Corporation), Chao-Shun Zhan (NVIDIA AI Technology Center, NVIDIA Corporation), Andy Liao (NVIDIA AI Technology Center, NVIDIA Corporation), Virginia Chen (NVIDIA AI Technology Center, NVIDIA Corporation), Johnson Sun (NVIDIA AI Technology Center, NVIDIA Corporation), Pika Wang (NVIDIA AI Technology Center, NVIDIA Corporation), Richard Huang (NVIDIA AI Technology Center, NVIDIA Corporation), Jiun-Cheng Jiang (NVIDIA AI Technology Center, NVIDIA Corporation), Ting-Yuan Liu (Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, Master Program for Digital Health Innovation, China Medical University, Taichung, Taiwan), Hsing-Fang Lu (Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan), Ray Y. Lee (AI-Driven Genomic Medicine and Drug Discovery Lab, China Medical University Hospital, Taichung, Taiwan), Chi-Chou Liao (Department of Medical Research, China Medical University Hospital, Taichung, Taiwan), Simon See (NVIDIA AI Technology Center, NVIDIA Corporation), Fuu-Jen Tsai (Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung, Taiwan)
arXiv AI
Aug 11

CliniCARE-Bench: Clinical Calibrated Audit of Medical Reasoning in EHR

arXiv:2608. 07796v1 Announce Type: new Abstract: Large language models perform strongly on medical knowledge benchmarks, but reliable clinical deployment requires agents to conduct defensible investigations over heterogeneous, longitudinal records: determining what evidence is needed, retrieving and reconciling structured and free-text data, grounding conclusions in verifiable evidence, and deferring cases that cannot be resolved reliably.

By Veronica Chatrath, Bryan Zhu, George Pu, Jingxuan Fan, Apaar Shanker, Varun Ursekar, Anahita Sharma, Jason Qin, Keqi Han, Soham Dinesh Tiwari, Soham Dan, Vijay Kalmath, Yuan Li, Daniel Yue Zhang, Chenguang Wang, Zainab Doctor, Zhijun Yin, Nigam H. Shah, Yuan Xue
arXiv AI
Jun 17

AIPatient Arena: EHR-grounded evaluation of large language models in end-to-end clinical consultation workflows

arXiv:2606. 17474v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly considered for use in clinical consultation tasks, yet most medical evaluations remain static, single-turn, or narrowly outcome-based, limiting their ability to reflect the sequential, uncertain, and interactive nature of real-world care.

By Jiahui Niu, Huizi Yu, Wenkong Wang, Guangxin Dai, Jingxian He, Xiang Li, Zhiying Liang, Xinxin Lin, Kent CY So, Bryan YP Yan, Yun Kwok Wing, Yanqiu Xing, Xin Ma, Lizhou Fan
arXiv AI
Jun 24

A global log for medical AI

arXiv:2510. 04033v2 Announce Type: replace Abstract: Modern computer systems rely on syslog, a universal protocol that records critical events across heterogeneous infrastructure.

By Ayush Noori, Aaron E. Boussina, Hai Ho Bich, James Anibal, Julia Maslinski, Manuel Burger, Martin Faltys, Adam Rodman, Alan Karthikesalingam, Alessandro Blasimme, Annelia Itwaru, Ben Kaplan, Bilal A. Mateen, Christopher A. Longhurst, Daniel Yang, Dave deBronkart, Effy Vayena, Fedor Sergeev, Gauden Galea, Ha Thi Hai Duong, Harold F. Wolf III, Jacob Waxman, Joerg C. Schefold, Joshua C. Mandel, Juliana Rotich, Kenneth D. Mandl, Lily Poursoltan, Maryam Mustafa, Melissa Miles, Nigam H. Shah, Noa Dagan, Pavan Bodanki, Peter Lee, Philipp Koralus, Prathamesh Parchure, Prem Timsina, Ran D. Balicer, Robert Korom, Scott Mahoney, Seth Hain, Tien Yin Wong, Trevor Mundel, Vivek Natarajan, Ankit Sakhuja, Benjamin Glicksberg, C. Louise Thwaites, Gunnar R\"atsch, Karandeep Singh, David A. Clifton, Isaac S. Kohane, Marinka Zitnik
arXiv AI
Jul 14

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy

arXiv:2607. 11175v1 Announce Type: new Abstract: The growing ability of large language models and vision language models to jointly interpret and reason over images and text is reshaping medical agents, moving them from task specific predictors toward autonomous systems that perceive, reason, plan, remember, and act in clinical environments.

By Chunzheng Zhu, Lei Tian, Bohan Tan, Ziqi Zhou, Yuxuan Sun, Yijun Wang, Chengchao Lv, Yilin Wen, Yijun He, Jinghao Lin, Yihang Chen, Cheewei Tan, Qianshan Wei, Lei Zhao, Bin Pu, Kenli Li, Yuan Xue, Jianxin Lin
arXiv AI
Jun 19

MedRLM: Recursive Multimodal Health Intelligence for Long-Context Clinical Reasoning, Sensor-Guided Screening, Evidence-Grounded Decision Support, and Community-to-Tertiary Referral Optimization

arXiv:2606. 20164v1 Announce Type: cross Abstract: Real-world clinical decision support requires reasoning over heterogeneous and longitudinal patient information rather than answering isolated medical questions.

By Aueaphum Aueawatthanaphisut