AIMC Topic: Diarrhea

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Predictive modeling and socioeconomic determinants of diarrhea in children under five in the Amhara Region, Ethiopia.

Frontiers in public health Aug 1, 2024
BACKGROUND: Diarrheal disease, characterized by high morbidity and mortality rates, continues to be a serious public health concern, especially in developing nations such as Ethiopia. The significant burden it imposes on these countries underscores t...
Diarrhea Logistic Models Socioeconomic Factors Ethiopia Male Infant Child, Preschool Health Surveys Humans Machine Learning Female Infant, Newborn Risk Factors Adult
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Exploring Machine Learning Algorithms to Predict Diarrhea Disease and Identify its Determinants among Under-Five Years Children in East Africa.

Journal of epidemiology and global health Jul 29, 2024
BACKGROUND: The second most common cause of death for children under five is diarrhea. Early Predicting diarrhea disease and identify its determinants (factors) using an advanced machine learning model is the most effective way to save the lives of c...
Humans Machine Learning Algorithms Infant Child, Preschool Diarrhea Female Logistic Models Infant, Newborn Africa, Eastern Risk Factors Male
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Interpretable machine learning models for predicting the incidence of antibiotic- associated diarrhea in elderly ICU patients.

BMC geriatrics May 24, 2024
BACKGROUND: Antibiotic-associated diarrhea (AAD) can prolong hospitalization, increase medical costs, and even lead to higher mortality rates. Therefore, it is essential to predict the incidence of AAD in elderly intensive care unit(ICU) patients. Th...
Diarrhea Male Middle Aged China Incidence Humans Female Machine Learning Retrospective Studies Aged Anti-Bacterial Agents Intensive Care Units Aged, 80 and over
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Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

Frontiers in immunology Mar 1, 2024
, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis,...
Diarrhea Adjuvants, Immunologic Adjuvants, Pharmaceutic Vaccines Aeromonas hydrophila Humans Artificial Intelligence Machine Learning Epitopes, T-Lymphocyte Bacterial Toxins Travel Pore Forming Cytotoxic Proteins
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Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.

BMC infectious diseases Feb 26, 2024
BACKGROUND: Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance.
Meteorological Concepts Neural Networks, Computer Public Health Incidence Humans Diarrhea
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Isolation and Pathogenicity Analysis of a G5P[23] Porcine Rotavirus Strain.

Viruses Dec 22, 2023
(1) Background: Group A rotaviruses (RVAs) are the primary cause of severe intestinal diseases in piglets. Porcine rotaviruses (PoRVs) are widely prevalent in Chinese farms, resulting in significant economic losses to the livestock industry. However,...
Rotavirus Animals Swine Virulence China Rotavirus Infections Diarrhea
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Predicting diarrhoea outbreaks with climate change.

PloS one Apr 19, 2022
BACKGROUND: Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity ...
Diarrhea Climate Change Humans Neural Networks, Computer Machine Learning Disease Outbreaks
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Identification of Risk Factors and Symptoms of COVID-19: Analysis of Biomedical Literature and Social Media Data.

Journal of medical Internet research Oct 2, 2020
BACKGROUND: In December 2019, the COVID-19 outbreak started in China and rapidly spread around the world. Lack of a vaccine or optimized intervention raised the importance of characterizing risk factors and symptoms for the early identification and s...
Humans Machine Learning Oxygen Inhalation Therapy Myalgia Social Media Betacoronavirus Risk Factors Cough Pneumonia, Viral Disease Outbreaks Publications Diarrhea Data Collection Fever Headache Pandemics Antiviral Agents Dyspnea Coronavirus Infections COVID-19 Fatigue Retrospective Studies SARS-CoV-2
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Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease Jun 8, 2020
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...
ROC Curve Logistic Models Area Under Curve Bayes Theorem Clostridioides difficile Tertiary Care Centers Aged Clostridium Infections Forecasting Male Anti-Bacterial Agents Humans Middle Aged Retrospective Studies Machine Learning Diarrhea Female
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Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis Jun 18, 2019
Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We applied machine learning to identify the best predictors of amyloidosis in rhesus macaques from availabl...
Cholesterol, LDL Machine Learning Gastrointestinal Neoplasms Diarrhea Biomarkers Endometriosis Humans Macaca mulatta Risk Factors Adenocarcinoma Disease Models, Animal Animals Colitis Cholesterol, HDL Serum Amyloid A Protein Retrospective Studies Models, Statistical Male Amyloidosis Case-Control Studies Female Triglycerides Arthritis Wounds and Injuries
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