Infectious Disease

Public Health

Latest AI and machine learning research in public health for healthcare professionals.

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KESOZI Digital Twin: Physics-Informed Neural Network for Independent Estimation and Prediction of Childhood Diarrheal Disease Burden in Kenya, Somaliland, and Zimbabwe

Childhood diarrheal disease remains a leading cause of morbidity and mortality among children under five years in sub-Saharan Africa, particularly in settings affected by inadequate sanitation, climate variability, malnutrition, and limited healthcare access. Conventional forecasting approaches are often constrained by sparse surveillance data, weak spatial representation, and limited incorporatio...

Simple cumulative weighting of routine surveillance data identifies epidemic wave origins more accurately than a large language model: evidence from eight COVID-19 waves in Japan

Identifying the origin of an emerging epidemic wave within days of onset could enable targeted response before national spread, yet current methods rely on genomic sequencing that lags clinical detection by 2-4 weeks. We analysed daily COVID-19 cases from Japan's 47 prefectures across eight waves (2020-2023), aggregated into 11 regional blocks. Wave onset was defined by the first difference of the...

The AFRIDIARRHEA multimodal fusion framework for Estimating the Burden of Diarrheal Diseases Among Children Under Five in Kenya, Zimbabwe, and Somaliland

Background: Accurate estimation of childhood diarrheal disease burden in Africa remains challenging because of limited surveillance, incomplete mortal...

SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images

Liver fibrosis is a major cause of death in low- and middle-income country contexts. In rural, poor areas of sub-Saharan Africa, schistosomiasis is an...

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune a...

Development and Validation of a Machine Learning Model to Predict Prognosis in Patients with Advanced Head and Neck Cancer

Importance Prognostic tools beyond staging are needed to guide treatment and counseling in head and neck squamous cell carcinoma (HNSCC). Objective To...

Future Pandemics: AI-Designed Diagnostic Assays for Detection of Andes Orthohantavirus (ANDV) Associated with the 2026 MV Hondius Outbreak

Andes orthohantavirus (ANDV), the primary etiological agent of hantavirus pulmonary syndrome (HPS) in South America, is uniquely capable of limited hu...

Glycemic response trajectories on metformin monotherapy in real-world diabetes care

Objectives: Diabetes affects over 500 million people globally and glycemia is inadequately managed. Metformin is the most frequently prescribed initia...

Cumulative In-Context Learning versus Simple Historical Weighting for Real-Time Geographic Origin Identification of Ongoing Epidemic Waves: A Comparative Evaluation Using Eight COVID-19 Waves in Japan

Background: Identifying the geographic origin of epidemic waves early is critical for targeted public health responses. Conventional statistical metho...

Interpreting the WaveSeekerNet model to reveal the evolution and biology of influenza A virus

Background Influenza A virus (IAV) is a major public health burden, causing seasonal epidemics and occasional pandemics. Its transmission from avian s...

Spatio-temporal machine learning for multi-horizon prediction of bluetongue outbreaks

Reliable early warning of infectious disease outbreaks remains a major challenge for surveillance systems, particularly for vector-borne pathogens who...

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 ...

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 ...

Development and validation of a digital pathology artificial intelligence (DPAI)-based biomarker predicting risk of Gleason grade group reclassification for patients who are candidates for active surveillance

Aims Active surveillance (AS) allows selected men with localized prostate cancer to defer curative therapy and reduce treatment morbidity. Conversion ...

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...

Estimating the Presence and Abundance of Aedes Albopictus in Europe Using Neural Networks

Aedes albopictus is an invasive mosquito species transmitting dengue, chikungunya, Zika and other arboviruses. Its ongoing geographical expansion acro...

Simulating population compliance with pandemic interventions using large language models

Effective pandemic response requires accurate modeling of population compliance with non-pharmaceutical interventions (NPIs), yet most epidemic models...

Prediction of Rectal Cancer Regrowth from Longitudinal Endoscopy

Clinical trial studies indicate benefit of watch-and-wait (WW) surveillance for patients with rectal cancer showing a complete or near clinical respon...

May 13 2026 2605.12855v1
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...

May 12 2026 2605.11900v1
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...

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