Infectious Disease

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

BACKGROUND: Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development process of sepsis but also related to poor prognosis of sepsis. We aimed to establish a machine learning (ML) model to predict the 28-day mortality risk of patients with SIC. METHODS: We collected data for model training from the Medical Information Mart for Intensive Care IV Database version 2.2 to ...

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

BACKGROUND: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patients; however, its predictive value for sepsis in the elderly remains underexplored. METHODS: This retrospective cohort study used the data from the MIMIC-IV database. The primary outcome was 28-day ICU mortality in elderly patients with sepsis. We used multivariate logistic regression, restricted cub...

Field evaluation of drone and AI assisted larval source management in Ghana.

BACKGROUND: Malaria remains a major public health burden in sub-Saharan Africa. In Ghana, in particular, larval source management (LSM) is increasingl...

Construction of a depression risk prediction model for hepatitis B patients based on machine learning strategy.

BACKGROUND: Hepatitis B (HBV) is a chronic viral infection that can lead to cirrhosis, liver failure, and liver cancer, and has a profound impact on t...

The phenomenal binding problem for neural networks.

Our aim is to explore neural network mechanisms for phenomenal binding, i.e. combining micro-units of information into the macro-scale conscious exper...

Machine learning-based COVID-19 prognostic models lag behind in reporting quality: findings from a TRIPOD/TRIPOD + AI systematic review.

BACKGROUND: Reporting of COVID-19 prognostic models frequently falls short of established standards. The TRIPOD checklist and its 2024 AI extension (T...

Mechanistic principles of antimicrobial peptides uncovered by charge density-based machine learning.

Antimicrobial peptides (AMPs) are emerging as potent alternatives to conventional antibiotics, yet their diverse nature due to divergent mechanisms of...

Fairness Correction in COVID-19 Predictive Models Using Demographic Optimization: Algorithm Development and Validation Study.

BACKGROUND: COVID-19 forecasting models have been used to inform decision-making around resource allocation and intervention decisions, such as hospit...

Evaluation of an Artificial Intelligence Conversational Chatbot to Enhance HIV Preexposure Prophylaxis Uptake: Development and Usability Internal Testing.

BACKGROUND: The HIV epidemic in the United States disproportionately impacts gay, bisexual, and other men who have sex with men (MSM). Despite the eff...

Predicting genetic evolution of viruses to identify suitable vaccines using artificial intelligence.

The evolution of the viruses is rapidly becoming a global challenge to the creation of vaccines since the new variants are often capable of escaping t...

Machine Learning Models for Predicting Stroke-Associated Pneumonia: A Systematic Review and Meta-Analysis.

Stroke-associated pneumonia (SAP) is a frequent and severe complication following stroke. Recently, several machine learning (ML) models have been dev...

Explainable AI for critical care: a systematic review of interpretable models for sepsis and ICU mortality prediction.

Compost fermented with thermophilic Bacillaceae reduces heat stress-induced mortality in laying hens through gut microbial modulation.

BACKGROUND: Heat stress (HS) adversely affects poultry health and productivity. Recently, it has been suggested that the gut microbiota may play a rol...

Machine learning-based prediction of acute and complicated appendicitis using readily available data in low-resource settings.

BACKGROUND: Acute appendicitis often presents diagnostic challenges, especially in pediatric and elderly patients. Delays can cause serious complicati...

Open-surface digital ELISA enabled by magnetic trapping and deep learning for rapid and highly sensitive detection of African swine fever.

African swine fever (ASF), a highly fatal and contagious animal disease caused by ASF virus, leads to substantial economic losses. Early detection is ...

A computational approach for classification of HIV drug resistance based on the self-consistent extreme classifier.

BACKGROUND AND OBJECTIVES: The development of viral resistance can significantly reduce the effectiveness of therapy. Human immunodeficiency virus typ...

Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.

Aerobic denitrifying bacteria are increasingly recognized for nitrogen removal in deep drinking-water reservoirs, yet how dissolved oxygen (DO) gradie...

Causal machine learning with interpretability deciphers the impact of micropollutants and socioeconomic factors on ARGs in Chinese urban drinking water.

The widespread co-occurrence of antibiotic resistance genes (ARGs) with diverse micropollutants in drinking water distribution systems poses a critica...

Benchmark evaluation of deepseek AI models in antibacterial clinical decision-making for infectious diseases.

BACKGROUND: Antimicrobial resistance (AMR) poses a global threat to public health, though AI models have shown transformative potential in combating A...

A qualitative study assessing the acceptability of a multi-agent AI Chatbot for providing HIV and mental health support among men who have sex with men and transgender women in KwaZulu-Natal, South Africa.

BACKGROUND: Transgender women (TGW) and men who have sex with men (MSM) are disproportionately affected by human immunodeficiency virus (HIV) and ment...