Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 71,951 to 71,960 of 235,116 articles
Reply to 'Risk stratification of cutaneous melanoma using deep learning on whole slide images'.
Journal of the European Academy of Dermatology and Venereology : JEADV
Oct 3, 2025
The current research status of non-destructive testing technologies for egg quality: internal freshness - a review.
British poultry science
Oct 3, 2025
1. Traditional methods of assessing egg freshness, such as sensory evaluation and specific gravity testing, are labour-intensive and destructive. However, non-destructive testing (NDT) technologies offer significant advantages in terms of speed, accu... read more
Roadmap for Representative Artificial Intelligence Models for Thyroid Cancer.
The Laryngoscope
Oct 3, 2025
Artificial intelligence (AI) models in thyroid cancer are often not generalizable due to biased or non-representative training and validation datasets. We propose a four-stage roadmap emphasizing representative data collection, inclusion of contextua... read more
Sysmex Cell Population Data for Diagnosing Infection in Patients With Suspected Sepsis in the Emergency Department.
International journal of laboratory hematology
Oct 3, 2025
OBJECTIVES: Early diagnosis of suspected sepsis is crucial to improve patient survival. Cell population (CP) data, a set of leucocyte research parameters from hematology instruments, has a potential as markers for infection. The aim of this study was... read more
Brain metabolic imaging with 18 F-PET-CT and machine-learning clustering analysis reveal divergent metabolic phenotypes in patients with amyotrophic lateral sclerosis.
European journal of nuclear medicine and molecular imaging
Oct 3, 2025
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by significant clinicopathologic heterogeneity. This study aimed to identify distinct ALS phenotypes by integrating brain 18 F-fluorodeoxyglucose posi... read more
Real-time fatigue monitoring system for motorcycle riders using sensors and a random forest algorithm.
International journal of occupational safety and ergonomics : JOSE
Oct 3, 2025
Fatigue is a major determinant of motorcycle accidents, posing a critical threat to road safety by impairing riders' psychophysiological performance and increasing the crash risk. This study introduces a real-time fatigue monitoring system specifical... read more
Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model.
Molecular psychiatry
Oct 3, 2025
Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due t... read more
Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications.
Journal of medical radiation sciences
Oct 3, 2025
Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain a potential barrier to participation. This scoping review explores existing models estimating long-... read more
Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History-Findings From a Machine Learning Analysis of Speech Data.
European eating disorders review : the journal of the Eating Disorders Association
Oct 3, 2025
OBJECTIVE: Eating disorder (ED) history may impact mother-child communication during mealtimes and contribute to transgenerational transmission of ED. This study employed machine learning (ML) to identify speech characteristics during mother-child fe... read more
Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions.
International orthodontics
Oct 3, 2025
OBJECTIVES: The aim of this study was to develop a machine-learning model to assist in treatment decision-making for surgery, camouflage, and growth modulation in Class II malocclusion patients and to evaluate its validity and reliability. MATERIAL A... read more
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- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
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- IEEE transactions on neural networks and learning systems 927
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