Infectious Disease

Open-source computational pipeline automatically flags instances of acute respiratory distress syndrome from electronic health records

Physicians, particularly intensivists, face information overload and decision fatigue, underscoring the need for automated diagnostic tools. Acute Respiratory Distress Syndrome (ARDS) affects over 10% of critical care patients, with over 40% mortality rate, yet is only recognized in 30-70% of cases in clinical settings. We present a reproducible computational pipeline that automates ARDS adjudicat...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it is impossible to draw up detailed plans for every pathogen with epidemic potential. We set out to try to simplify this process by reviewing the epidemiology of a range of pathogens with pandemic potential and seeing whether they fall into groups with...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a major ...

Octopi 2.0: Point-of-care Multi-disease Detection and Diagnosis via Edge AI Imaging Platform

Access to quantitative, robust, and affordable diagnostic tools is essential to address the global burden of infectious diseases. While manual microsc...

Proteome-wide autoantibody screening and holistic autoantigenomic analysis unveil COVID-19 signature of autoantibody landscape

This study presents “aUToAntiBody Comprehensive Database (UT-ABCD)”, a comprehensive catalog of autoantibody profiles in 284 human individuals. The su...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms, aiding risk stratification and guiding patient ma...

Development and Prospective Implementation of a Large Language Model based System for Early Sepsis Prediction

Sepsis is a dysregulated host response to infection with high mortality and morbidity. Early detection and intervention have been shown to improve pat...

Predicting community-acquired pneumonia outcome using time series data and machine learning

Community-acquired pneumonia (CAP) is an acute respiratory condition associated with high mortality in adult populations and is potentially more serio...

NTDscope: A multi-contrast portable microscope for disease diagnosis

Accurate diagnostics are essential for disease control and elimination efforts. However, access to diagnostics for neglected tropical diseases (NTDs) ...

Transformer-based artificial intelligence on single-cell clinical data for homeostatic mechanism inference and rational biomarker discovery

Artificial intelligence (AI) applied to single-cell data has the potential to transform our understanding of biological systems by revealing patterns ...

Suitability of just-in-time adaptive intervention in post-COVID-19-related symptoms: A systematic scoping review

Patients with post-COVID-19-related symptoms require active and timely support in self-management. Just-in-time adaptive interventions (JITAI) seem pr...

Development of a Risk Prediction Model for Sepsis-Related Delirium Based on Multiple Machine Learning Approaches and an Online Calculator

Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant...

Detection of patient metadata in published articles for genomic epidemiology using machine learning and large language models

Patient metadata exist in published articles, but are often dis-connected from genome sequences in databases, limiting their utility for genomic epide...

Comparative Evaluation of Time Series Forecasting Approaches for Facility-Level Antibiotic Resistance Outcomes in the Veterans Health Administration

Antibiotic resistance is a critical public health threat, particularly in hospital settings where vulnerable populations face heightened risks of infe...

Conformal Prediction and Venn-ABERS Calibration for Reliable Machine Learning-Based Prediction of Bacterial Infection Focus

Finding the focus of bacterial infections can be challenging, especially for hospitalised patients. Conventional microbiological diagnostic methods ar...

Automated diagnosis of usual interstitial pneumonia on chest CT via the mean curvature of isophotes

To test whether the mean curvature of isophotes (MCI), a geometric image transformation, can be used to improve automatic detection on chest CT of Usu...

A simple feed forward neural network to predict the 2025 outbreak of measles in the USA

Measles is a highly contagious viral disease associated with a variety of severe complications. Since 1963, widespread usage of a highly effective vac...

Pulmonary tuberculosis prediction using CAD4TB artificial intelligence (computer-aided detection for tuberculosis) based on thoracic x-ray photos among Indonesian subjects in hospital

Tuberculosis remains a major global health concern, particularly in high-burden countries where early detection is essential but often limited by insu...

AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH, and AIH

Annotation of liver biopsies, for disease staging is increasingly aided by digital pathology, however existing systems do not quantify inflammation an...

Artificial Intelligence-based Diagnosis of Kaposi Sarcoma using Photographs in Dark-skinned Patients

Advanced-stage disease at the time of diagnosis, with resultant high mortality, is among the most urgent issues for HIV-related Kaposi sarcoma (KS) in...