Surveillance

Professionalism Pulse: Development and Validation of a Natural Language Processing Pipeline and Dashboard for Safety Culture Surveillance in NYC Health + Hospitals

Background: Professionalism and effective communication are foundational determinants of patient safety and quality of care. Unprofessional behaviors frequently serve as active precursors to adverse clinical events. However, proactive organizational surveillance is often hindered because incident feedback exists primarily as unstructured, free-text data. This study aimed to develop and validate a ...

A digital twin for hospital antimicrobial resistance forecasting and constrained intervention optimisation

Hospital antimicrobial resistance (AMR) emanates from an array of complex interactions between patient turnover, heterogeneous patient--staff contact patterns, antibiotic-driven within-host selection, and imperfect surveillance. We present a hospital AMR digital twin that combines mechanistic simulation with temporal graph learning to forecast resistance emergence from evolving daily contact netwo...

Large-Scale Assessment of Animal-to-Human Drug Translation Using Natural Language Processing

Background: Large-scale estimates of animal-to-human drug translation and the study characteristics associated with successful translation remain limi...

Antimicrobial peptide databases and prediction tools: Toward a standard evaluation framework

Antimicrobial resistance (AMR) has a profound impact on animal and human health and is associated with substantial morbidity, mortality and public hea...

Predicting Distant Melanoma Metastasis at Diagnosis Using Machine Learning

Distant melanoma metastasis at the time of diagnosis is uncommon, but has major implications for patient prognosis and treatment selection. However, f...

Deep Learning for Automated Meningioma Segmentation: Toward Clinical Integration and Workflow Efficiency

Background: Meningiomas are the most common primary intracranial tumors in adults, and volumetric assessment increasingly guides surveillance and trea...

MonoPRIO: Adaptive Prior Conditioning for Unified Monocular 3D Object Detection

Monocular 3D object detection remains challenging because metric size and depth are underdetermined by single-view evidence, particularly under occlus...

Mobile Traffic Camera Calibration from Road Geometry for UAV-Based Traffic Surveillance

Unmanned aerial vehicles (UAVs) can provide flexible traffic surveillance where fixed roadside cameras are unavailable, costly, or impractical. Howeve...

Epidemiology-Informed Graph Neural Networks for Predicting and Interpreting Transmissible Hospital-Acquired Infections: A Retrospective Cohort and Simulation Study

Transmissible hospital-acquired infections (HAIs) arise from complex, time-varying interactions among patients, healthcare workers, and clinical envir...

ClaroAI-Bench: Evaluating Agentic Scientific Reproducibility on Real Biomedical Papers

We introduce ClaroAI-Bench, an evaluation suite for measuring AI agents' ability to reproduce computational findings from published biomedical researc...

Systematic toxicological study of PFOS/PFOA co-exposure driving prostate cancer: Core target identification, TME immune remodeling, and combination drug prediction

Background: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persisten...

Cadence: A Benchmark Evaluation of the Narrative Velocity Framework for Next Clinical Event Prediction in MIMIC-IV

Objective: How structured clinical features and cluster-semantic embeddings interact under self-distillation in EHR prediction models is unknown. Exis...

RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiology

Cancer screening is a reasoning task. A radiologist observes findings, compares them to prior scans, integrates clinical context, and reaches a diagno...

Simpler is not always better: Phylodynamic misspecification and deep-learning corrections

Phylodynamics bridges the gap between epidemiology and pathogen genetic data by estimating epidemiological parameters from time-scaled pathogen phylog...

Enhancing dengue diagnosis and surveillance by integrating machine learning technologies with the NS1 rapid test kit

Background. Dengue has been a major health threat globally in recent years. In particular, dengue incidences continue to increase annually and the epi...

Species-specific transformer models of bacterial gene order and content for genomic surveillance tasks

Transformer models enable functionally meaningful representation of complex biological data, such as nucleotide or protein sequences. Existing foundat...

Scalable machine learning improves resistance prediction and identifies novel determinants in Mycobacterium tuberculosis

Multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (MTB) represents a growing global health crisis, characterized by limite...

CladePredictor - MPXV: An alignment-free Artificial Intelligence-based classifier of complete and partial mpox virus genomes

Poxviruses constitute a threat to human health. Since 2022, two public health emergencies of international concern due to global spread of mpox viruse...

Generative diffusion models for spatiotemporal influenza forecasting

Forecasting infectious disease incidence can provide important information to guide public health planning, yet is difficult because epidemic dynamics...

Pediatric HIV Hotspots in Kenya: Machine Learning and Geostatistical Analysis for Enhanced Case Finding

Background Although Kenya's HIV programme has long prioritized high-burden counties for intensified paediatric interventions, a critical evidence gap ...