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Artificial intelligence-based framework for early detection of heart disease using enhanced multilayer perceptron.
Front Artif Intell
January 2025
Department of Computer Science and Artificial Intelligence, College of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia.
Cardiac disease refers to diseases that affect the heart such as coronary artery diseases, arrhythmia and heart defects and is amongst the most difficult health conditions known to humanity. According to the WHO, heart disease is the foremost cause of mortality worldwide, causing an estimated 17.8 million deaths every year it consumes a significant amount of time as well as effort to figure out what is causing this, especially for medical specialists and doctors.
View Article and Find Full Text PDFMesonephric-like adenocarcinoma of the ovary: a case study.
J Surg Case Rep
January 2025
Department of Pathology of the National Institute of Oncology, Ibn Sina University Hospital Center, Allal Al Fassi Avenue, Rabat 10100, Morocco.
Mesonephric-like adenocarcinoma (MLA) is a rare and newly recognized subtype of ovarian and endometrial carcinomas, introduced in the 2020 World Health Organization Classification. This tumor likely originates from Müllerian-derived tissues and often mimics more common ovarian cancers, leading to frequent misdiagnosis. This case study details a 36-year-old woman who presented with urinary symptoms following a hysterectomy.
View Article and Find Full Text PDFAssociations between degree of food processing and all-cause and cause-specific mortality: a multicentre prospective cohort analysis in 9 European countries.
Lancet Reg Health Eur
March 2025
Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Background: Ultra-processed food (UPF) consumption has been linked with higher risk of mortality. This multi-centre study investigated associations between food intake by degree of processing, using the Nova classification, and all-cause and cause-specific mortality.
Methods: This study analyzed data from the European Prospective Investigation into Cancer and Nutrition.
Identifying targets for antibiotic stewardship interventions in pediatric patients in Punjab, Pakistan: point prevalence surveys using AWaRe guidance.
Front Pediatr
January 2025
Department of Public Health Pharmacy and Management, School of Pharmacy, Sefako Makgatho Health Sciences University, Ga-Rankuwa, South Africa.
Introduction: Surveillance of antibiotic use is crucial for identifying targets for antibiotic stewardship programs (ASPs), particularly in pediatric populations within countries like Pakistan, where antimicrobial resistance (AMR) is escalating. This point prevalence survey (PPS) seeks to assess the patterns of antibiotic use in pediatric patients across Punjab, Pakistan, employing the WHO AWaRe classification to pinpoint targets for intervention and encourage rational antibiotic usage.
Methods: A PPS was conducted across 23 pediatric wards of 14 hospitals in the Punjab Province of Pakistan using the standardized Global-PPS methodology developed by the University of Antwerp.
Liver fibrosis classification on trichrome histology slides using weakly supervised learning in children and young adults.
J Pathol Inform
January 2025
Cincinnati Children's AI Imaging Research (CAIIR) Center, Cincinnati, OH, United States.
Background: Traditional liver fibrosis staging via percutaneous biopsy suffers from sampling bias and variable inter-pathologist agreement, highlighting the need for more objective techniques. Deep learning models for disease staging from medical images have shown potential to decrease diagnostic variability, with recent weakly supervised learning strategies showing promising results even with limited manual annotation.
Purpose: To study the clustering-constrained attention multiple instance learning (CLAM) approach for staging liver fibrosis on trichrome whole slide images (WSIs) of children and young adults.
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