Irritable Bowel Syndrome

Development of a machine learning prediction model for overactive bladder in female nurses: the NURS study.

PURPOSE: To develop and internally validate interpretable machine-learning models for identifying individuals with a higher probability of overactive bladder (OAB) among female nursing professionals. METHODS: A total of 13,191 female nurses participating in the Nurse Urinary Related Health Study were included and divided into training (70%) and testing (30%) cohorts. Seven distinct machine learnin...

XGBoost-based early warning framework for farm-level PED risk using meteorological and herd management variables.

Porcine epidemic diarrhea (PED) imposes substantial economic losses on the global swine industry, with outbreaks driven by the complex interplay of meteorological conditions and herd management practices. A farm-level risk prediction framework was developed by integrating meteorological and reproductive performance variables from commercial pig farms in southern China. A triangulated variable sele...

Jianpi Bushen Qingchang Huashi formula alleviates DSS-induced colitis through butyrate-associated HDAC1 inhibition and Th17/Treg homeostasis.

ETHNOPHARMACOLOGICAL RELEVANCE: Jianpi Bushen Qingchang Huashi Formula (JBQHF) is a traditional Chinese medicine compound of nine herbal ingredients c...

Machine learning-based prediction of fever among under-five children in Ethiopia: A national-level study.

Fever remains a leading cause of morbidity and mortality among children under the age of five, particularly in low-resource settings like Ethiopia. Mo...

Automated detection of Eimeria tenella from hematoxylin and eosin-stained chicken cecal tissues using YOLOv4-based deep learning: A proof-of-concept study.

Avian coccidiosis is a disease primarily characterized by diarrhea caused by intestinal infection with protozoa of the genus Eimeria, causing signific...

AI-Assisted cardiomegaly screening via implicit morphological inference and human-in-the-loop validation.

Cardiomegaly screening via manual Cardiothoracic Ratio (CTR) measurement remains a clinical bottleneck, while contemporary deep learning solutions oft...

Toward disease-associated fecal microbiome signatures for domestic mammals.

Conserved fecal microbiome signatures of intestinal diseases across domestic mammals offer a non-invasive avenue to monitor animal health and advance ...

The effectiveness of a plant-based milk with fermented brown rice on constipation symptoms via gut microbiota modulation: a double-blind randomized controlled trial.

PURPOSE: To evaluate the effects of a plant-based milk with fermented brown rice on constipation symptoms in patients with functional constipation and...

Impact of meteorological factors on other infectious diarrhea in mainland China: comprehensive risk assessment, forecasting and early warning.

Other infectious diarrhea (OID) is a major public health burden in China and a typical weather-sensitive disease, yet nationwide evidence that links c...

Gastrointestinal endoscopic image classification using a hybrid modified inception network and a customized vision transformer with tree growth feature selection.

The Gastrointestinal (GI) tract plays a vital role in digestion by breaking down food into essential nutrients. Disorders such as bleeding lesions, ul...

Geospatial variation and machine learning approaches to predict open defecation practice in Zambia.

BACKGROUND: Open defecation is the disposal of human feces in fields, bushes, forests, open waterways, beaches, and other open areas. It worsens the e...

Integrating machine learning and WGCNA to identify core candidate genes and decipher immune-related molecular networks in TcdA/TcdB-associated CDI.

Clostridioides difficile infection (CDI) remains a leading cause of healthcare-associated diarrhea and is characterized by high recurrence rates and i...

The impact of an artificial intelligence (AI)-assisted education program on mental health, social support and quality of life in older individuals with head and neck cancer: study protocol of a randomized controlled trial.

BACKGROUND: Head and neck cancer (HNC) is a common malignant tumor, and its treatment often leads to functional impairments in speech, swallowing, and...

Fully Automated Colon Delineation and Volume Estimation in T2-Weighted MRI with a 2D U-Net.

Artificial intelligence has the potential to provide an objective, accurate and fast evaluation of the colon for clinical assessment of gastrointestin...

Biological applications and future perspectives of bioactive compounds as pig feed additives.

Restrictions or prohibitions on the use of antibiotics in pig feed for growth promotion have been introduced in many countries. Bioactive compounds (B...

Time-Dynamic AI Models to Predict Quality of Life in Patients With Breast Cancer: Development and Validation Study Using the EORTC BALANCE Cohort.

BACKGROUND: Patients with breast cancer often experience health-related quality of life (HRQoL) impairments that remain difficult to predict on an ind...

Multimodal brain imaging-based classification of functional constipation subtypes using machine learning.

Functional constipation (FC) is a common gastrointestinal condition often accompanied by anxiety and depression status (FCAD). Gastrointestinal sympto...

Screening and dynamic change study of microbial and metabolite markers for calf diarrhea based on multi-omics and machine learning.

UNLABELLED: Neonatal calf diarrhea is a leading cause of calf mortality and substantial economic loss in the livestock industry, yet the dynamic micro...

Modeling diarrhea in children under five in Somaliland: A machine learning analysis using SLDHS 2020 data.

BACKGROUND: Diarrhea remains a leading cause of morbidity and mortality among children under five years of age, particularly in low- and middle-income...

Metagenomic analysis of the gut microbiota in Cryptosporidium-infected Tibetan sheep.

Cryptosporidium are important causative parasitic protozoa that cause gastrointestinal discomfort and diarrhea in humans and animals, posing a huge th...