AIMC Topic: Diarrhea

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Personalized azithromycin treatment rules for children with watery diarrhea using machine learning.

Nature communications Jul 1, 2025
We use machine learning to identify innovative strategies to target azithromycin to the children with watery diarrhea who are most likely to benefit. Using data from a randomized trial of azithromycin for watery diarrhea (NCT03130114), we develop per...
Humans Machine Learning Anti-Bacterial Agents Child, Preschool Child Diarrhea Treatment Outcome Azithromycin Precision Medicine Female Male Infant
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An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).

Scientific reports Apr 16, 2025
The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, remains a challenge. The Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) ( http://www.gutrhythm.com/public_database ) is a new source of el...
Digestive System Diseases Predictive Learning Models Vomiting Databases, Pharmaceutical Biological Clocks Electrodiagnosis Big Data Diarrhea ROC Curve Area Under Curve Feasibility Studies Humans Drug-Related Side Effects and Adverse Reactions Reproducibility of Results Gastrointestinal Tract Deep Learning Constipation Nausea
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A retrospective study using machine learning to develop predictive model to identify rotavirus-associated acute gastroenteritis in children.

PeerJ Apr 14, 2025
BACKGROUND: Rotavirus is the leading cause of severe dehydrating diarrhea in children under 5 years worldwide. Timely diagnosis is critical, but access to confirmatory testing is limited in hospital settings. Machine learning (ML) models have shown p...
India Support Vector Machine Decision Trees Bayes Theorem Rotavirus Rotavirus Infections Gastroenteritis Male Infant Child, Preschool Diarrhea Humans Machine Learning Retrospective Studies Female
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Interpretable machine learning-derived nomogram model for early detection of persistent diarrhea in Salmonella typhimurium enteritis: a propensity score matching based case-control study.

BMC infectious diseases Feb 10, 2025
BACKGROUND: Salmonella typhimurium infection is a considerable global health concern, particularly in children, where it often leads to persistent diarrhea. This condition can result in severe health complications including malnutrition and cognitive...
Humans Machine Learning Infant Case-Control Studies Child, Preschool Child Diarrhea Retrospective Studies Female Risk Factors Male Propensity Score Salmonella Infections Nomograms Salmonella typhimurium Enteritis Early Diagnosis
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Development of a one-step multiplex RT-qPCR method for rapid detection of bovine diarrhea viruses.

Frontiers in cellular and infection microbiology Jan 28, 2025
INTRODUCTION: Viral calf diarrhea poses a significant challenge to the cattle industry worldwide due to its high morbidity and mortality rates, leading to substantial economic losses. The clinical symptoms associated with various diarrhea pathogens o...
Kobuvirus Cattle Diseases Feces Torovirus Multiplex Polymerase Chain Reaction DNA Primers Reproducibility of Results Reverse Transcriptase Polymerase Chain Reaction Diarrhea Sensitivity and Specificity Bovine Virus Diarrhea-Mucosal Disease Diarrhea Viruses, Bovine Viral Animals Real-Time Polymerase Chain Reaction Cattle
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Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

BMC medical informatics and decision making Jan 15, 2025
BACKGROUND: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machin...
Child, Preschool Diarrhea Kenya Algorithms Female Male Infant Humans Machine Learning
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Allogenic faecal microbiota transplantation for antibiotic-associated diarrhoea in critically ill patients (FEBATRICE)-Study protocol for a multi-centre randomised controlled trial (phase II).

PloS one Dec 27, 2024
BACKGROUND: Exposure of critically ill patients to antibiotics lead to intestinal dysbiosis, which often manifests as antibiotic-associated diarrhoea. Faecal microbiota transplantation restores gut microbiota and may lead to faster resolution of diar...
Diarrhea Feces Gastrointestinal Microbiome Fecal Microbiota Transplantation Dysbiosis Prospective Studies Critical Illness Female Male Multicenter Studies as Topic Humans Randomized Controlled Trials as Topic Anti-Bacterial Agents Clinical Trials, Phase II as Topic
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Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.

BMC medical informatics and decision making Dec 2, 2024
INTRODUCTION: Stunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, de...
Female Male Infant Growth Disorders Child, Preschool Humans Diarrhea Machine Learning Rural Population Retrospective Studies Models, Statistical Kenya
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Development and internal validation of an artificial intelligence-assisted bowel sounds auscultation system to predict early enteral nutrition-associated diarrhoea in acute pancreatitis: a prospective observational study.

British journal of hospital medicine (London, England : 2005) Aug 19, 2024
An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-...
Auscultation ROC Curve Predictive Value of Tests Enteral Nutrition Pancreatitis Adult Male Middle Aged Diarrhea Artificial Intelligence Humans Prospective Studies Female Risk Factors Aged
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Identification of COL3A1 as a candidate protein involved in the crosstalk between obesity and diarrhea using quantitative proteomics and machine learning.

European journal of pharmacology Aug 8, 2024
BACKGROUND: Increasing epidemiologic studies have shown a positive correlation between obesity and chronic diarrhea. Nevertheless, the precise etiology remains uncertain.
Humans Machine Learning Female Adult Male Middle Aged Case-Control Studies Diarrhea Jejunum Collagen Type III Protein Interaction Maps Proteomics Obesity Caco-2 Cells
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