AIMC Topic: Humans

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Predicting mothers' exclusive breastfeeding for the first 6 months: Interface creation study using machine learning technique.

Journal of evaluation in clinical practice
BACKGROUND: Machine learning techniques (MLT) build models to detect complex patterns and solve new problems using big data.

Mechanical strength recognition and classification of thermal protective fabric images after thermal aging based on deep learning.

International journal of occupational safety and ergonomics : JOSE
. Currently, numerous studies have focused on testing or modeling to evaluate the safe service life of thermal protective clothing after thermal aging, reducing the risk to occupational personnel. However, testing will render the garment unsuitable f...

An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking ...

Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease.

The lancet. Gastroenterology & hepatology
Integrating artificial intelligence into inflammatory bowel disease (IBD) has the potential to revolutionise clinical practice and research. Artificial intelligence harnesses advanced algorithms to deliver accurate assessments of IBD endoscopy and hi...

Natural Language Processing to Identify Home Health Care Patients at Risk for Becoming Incapacitated With No Evident Advance Directives or Surrogates.

Journal of the American Medical Directors Association
OBJECTIVES: Home health care patients who are at risk for becoming Incapacitated with No Evident Advance Directives or Surrogates (INEADS) may benefit from timely intervention to assist them with advance care planning. This study aimed to develop nat...

Clinical evaluation of a machine learning-based dysphagia risk prediction tool.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: The rise of digitization promotes the development of screening and decision support tools. We sought to validate the results from a machine learning based dysphagia risk prediction tool with clinical evaluation.

CKG-IMC: An inductive matrix completion method enhanced by CKG and GNN for Alzheimer's disease compound-protein interactions prediction.

Computers in biology and medicine
Alzheimer's disease (AD) is one of the most prevalent chronic neurodegenerative disorders globally, with a rapidly growing population of AD patients and currently no effective therapeutic interventions available. Consequently, the development of ther...

AVBAE-MODFR: A novel deep learning framework of embedding and feature selection on multi-omics data for pan-cancer classification.

Computers in biology and medicine
Integration analysis of cancer multi-omics data for pan-cancer classification has the potential for clinical applications in various aspects such as tumor diagnosis, analyzing clinically significant features, and providing precision medicine. In thes...

Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology.

Computers in biology and medicine
Segmentation and classification of large numbers of instances, such as cell nuclei, are crucial tasks in digital pathology for accurate diagnosis. However, the availability of high-quality datasets for deep learning methods is often limited due to th...