Infectious Disease

SYSTEMS AND NETWORK BIOLOGY ANALYSIS COMBINED WITH MACHINE LEARNING IDENTIFIES KEY IMMUNE RESPONSE PROFILES AND POTENTIAL CORRELATES OF PROTECTION FOR THE M72/AS01E TUBERCULOSIS VACCINE

Tuberculosis claims around 1.5 million lives annually. The M72/AS01E vaccine candidate is an innovative effort demonstrating a 50% reduction in the incidence of active TB in adults. However, optimization and effective immunization strategies against TB depends heavily on precise identification of specific molecular signatures active in vaccine protection. In this study, we employed weighted gene c...

Domain Knowledge Augmented Contrastive Learning on Dynamic Hypergraphs for Improved Health Risk Prediction

Accurate health risk prediction is crucial for making informed clinical decisions and assessing the appropriate allocation of medical resources. While recent deep learning based approaches have shown great promise in risk prediction, they primarily focus on modeling the sequential information in Electronic Health Records (EHRs) and fail to leverage the rich mobility interactions among health entit...

Large language models’ interpretation homogeneity and text Analysis: Evaluating the utility of the global flu view platform for Influenza surveillance

The advent of Large Language Models (LLMs) has transformed natural language processing and offers new possibilities for analyzing qualitative data in ...

From Patient Voices to Policy: Data Analytics Reveals Patterns in Ontario’s Hospital Feedback

Patient satisfaction is a central measure of high-performing healthcare systems, yet real-world evaluations at scale remain challenging. In this study...

Towards AI-based Precision Rehabilitation via Contextual Model-based Reinforcement Learning

Stroke is a condition marked by considerable variability in lesions, recovery trajectories, and responses to therapy. Consequently, precision medicine...

A Multi-pathogen Hospitalization Forecasting Model for the United States: An Optimized Geo-Hierarchical Ensemble Framework

Accurate forecasting of infectious diseases is crucial for timely public health response. Ensemble frameworks have shown promising outcomes in short-t...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring electronic health records (EHR) data for clinical outco...

Predicting Hypertension Among HIV Patients on Antiretroviral Therapy in Rural Eastern Cape, South Africa Using Machine Learning

Hypertension continues to be a major challenge in developing countries like South Africa, as it significantly contributes to the cardiovascular diseas...

Surveying the Literature on Implementation Determinants and Strategies for HIV Structural Interventions: A Systematic Review Protocol

Despite improvements in HIV prevention, treatment, and surveillance, vast disparities remain in access, uptake, and adherence of evidence-based interv...

AI-Driven Early Detection of Severe Influenza in Jiangsu, China: A Deep Learning Model Validated Through The Design of Multi-Center Clinical Trials and Prospective Real-World Deployment

Influenza causes about 650,000 deaths worldwide each year, and the high mortality rate of severe cases is closely related to subjective bias in clinic...

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...

Generative AI Mitigates Representation Bias and Improves Model Fairness Through Synthetic Health Data

Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepre...

Alterations in the hepatic microenvironment following direct-acting antiviral therapy for chronic hepatitis C

Background and aims. The first direct-acting antivirals (DAAs) to treat the viral hepatitis C (HCV) became available in 2011. Despite numerous clinica...

A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), encompasses a range of symptoms persisting for weeks or months after the...

Designing AI-powered healthcare assistants to effectively reach vulnerable populations with health care services: A discrete choice experiment among South African university students

South African young adults are at increased risk for HIV acquisition and other non-communicable diseases and face significant barriers to accessing he...

Short-Term Mortality After Opioid Initiation Among Opioid-Naïve and Non-Naïve Patients with Dementia: A Retrospective Cohort Study

Despite the ongoing opioid epidemic, the mortality risk of opioid initiation in patients with dementia or mild cognitive impairment (MCI) remains unde...

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional micr...

Exploring multidrug resistance patterns in community-acquired E. coli urinary tract infections with machine learning

While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remai...

XGBoost-Based Prediction of ICU Mortality in Sepsis-Associated Acute Kidney Injury Patients Using MIMIC-IV Database with Validation from eICU Database

Sepsis-Associated Acute Kidney Injury (SA-AKI) leads to high mortality in intensive care. This study develops machine learning models using the Medica...

Foundation time series models for forecasting and policy evaluation in infectious disease epidemics

Epidemic forecasting and policy evaluation rely on mathematical models to predict infectious disease trends and assess the impact of public health pol...