ARMD‑Predict is a multi‑site machine‑learning system trained on 7.5 million culture‑antibiotic records from four academic medical centers to forecast antibiotic resistance before culture results are available. It offers two tiers of models: one set predicts susceptibility to individual antibiotics, while a hierarchical set first identifies the infecting organism and then its resistance profile. In internal testing, the models achieved median AUROCs of 0.77 for inpatient urine and 0.70 for inpatient blood cultures, and could flag a substantial proportion of ceftriaxone‑susceptible and resistant cases for narrower or broader therapy, respectively.
By Fateme Nateghi Haredasht, Nicholas P. Marshall, Wenyuan Chen, Lauren N. Cooper, Ziming Wei, Harrison Konsker, Jacob S. Chen, Michael Klompas, Cara McKenna, Richard J. Medford, Sanjat Kanjilal, Austin J. Schoeffler, Stephen P. Ma, Niaz Banaei, Steven M. Asch, Amy Chang, Stanley C. Deresinski, Mary K. Goldstein, Robert Tibshirani, Jonathan H. Chen
arXiv:2605.22611v2 Announce Type: replace
Abstract: Antimicrobial stewardship (AMS) is critical in pediatric intensive care units (PICUs), where diagnostic uncertainty often drives broad-spectrum ant...
By Niklas Raehse, Luregn J. Schlapbach, Daphn\'e Chopard
The study presents a cost‑sensitive XGBoost model that predicts ESBL‑producing Enterobacteriaceae at the time of culture ordering using 45 pre‑culture EHR features from 132,955 cultures across 12 hospitals. At 90% sensitivity the model achieves a 95.8% negative predictive value, potentially allowing carbapenem‑sparing therapy in non‑ICU settings while avoiding unnecessary broad‑spectrum treatment for 307 out of every 1,000 cultures, at the expense of 14 missed ESBL cases per 1,000. SHAP analysis highlights prior ESBL colonization as the strongest predictor, with minimal performance loss when socioeconomic deprivation features are omitted, supporting equitable bedside deployment.
By Aravind V. Kuruvikkattil, Lalitha Pranathi Pulavarthy, Rashmita Kudamala, Saptarshi Purkayastha
arXiv:2607. 04486v1 Announce Type: new Abstract: Diagnosing and monitoring diseases frequently involves the analysis of human biological samples, with blood analysis being pivotal.
By Ahmed M. Sayed (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Sondos A. Refaat (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Abdallah M. Mostafa (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Mariam S. El-Rahmany (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt), Ensaf Hussein Mohamed (Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt, School of Information Technology and Computer Science)
arXiv:2602. 22673v2 Announce Type: replace Abstract: Background: Antimicrobial resistance (AMR) is a global health threat.
By Md Tanvir Hasan Turja
arXiv:2606. 26561v1 Announce Type: new Abstract: Hepatitis C is a liver infection caused by a virus, which results in mild to severe inflammation of the liver.
By Abrar Alotaibi, Lujain Alnajrani, Nawal Alsheikh, Alhatoon Alanazy, Salam Alshammasi, Meshael Almusairii, Shoog Alrassan, Aisha Alansari
arXiv:2601.00175v3 Announce Type: replace
Abstract: Objective: Develop and evaluate machine learning (ML) models for predicting incident liver cirrhosis (LC) one and two years before diagnosis using...
By Zhuqi Miao, Ahmed G Qasem, Sujan Ravi, Jason T. Cheng, Abdulaziz Ahmed, Courtney W. Houchen, Sumayah Abed, Dilorom Azimdjanovna Zuparova, Abdulaziz Ahmed
arXiv:2601. 00175v2 Announce Type: replace Abstract: Objective: Develop and evaluate machine learning (ML) models for predicting incident liver cirrhosis (LC) one and two years prior to diagnosis using routinely collected electronic health record (EHR) data and benchmark their performance against the FIB-4 and APRI clinical scores.
By Zhuqi Miao, Ahmed G Qasem, Sujan Ravi, Jason T. Cheng, Abdulaziz Ahmed, Courtney W. Houchen, Sumayah Abed, Dilorom Azimdjanovna Zuparova, Abdulaziz Ahmed
Hepatitis C is a liver infection caused by a virus, which results in mild to severe inflammation of the liver. Over many years, hepatitis C gradually damages the liver, often leading to permanent scarring, known as cirrhosis.
arXiv:2606. 19183v1 Announce Type: cross Abstract: Large language models (LLMs) can make clinical decision support more accessible by interpreting free-text documentation, but their direct use as diagnostic engines is limited by sensitivity to prompts, information order, and plausible but incorrect outputs.
By Soheyl Bateni, Maryam Abdolali
arXiv:2509.23552v2 Announce Type: replace-cross
Abstract: Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance...
By Md. Saiful Bari Siddiqui, Nowshin Tarannum
arXiv:2608. 13617v1 Announce Type: new Abstract: Verifying whether clinical care follows evidence-based protocols is a natural neuro-symbolic problem, yet the safety-critical setting defeats either paradigm alone.
By Himanshu Tripathi, Kaushik Roy, Subash Neupane, Shahram Rahimi