AIMC Topic: Humans

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Monitoring strategies for continuous evaluation of deployed clinical prediction models.

Journal of biomedical informatics
OBJECTIVE: As machine learning adoption in clinical practice continues to grow, deployed classifiers must be continuously monitored and updated (retrained) to protect against data drift that stems from inevitable changes, including evolving medical p...

Cerebral aneurysm surgical training in the neuroendovascular era and its impact on the production of comfortable aneurysm surgeons.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: The increasing use of endovascular techniques has greatly decreased the number of intracranial aneurysms treated with open surgery. The objective of this study is to quantify chief residents' experience and comfort level with clipping of ...

Comparative analysis of semantic-segmentation models for screen film mammograms.

Computers in biology and medicine
Accurate segmentation of mammographic mass is very important as shape characteristics of these masses play a significant role for radiologist to diagnose benign and malignant cases. Recently, various deep learning segmentation algorithms have become ...

The revolutionary impact of 6G technology on empowering health and building a smart society: A scoping review.

Computers in biology and medicine
OBJECTIVE: This scoping review investigates the potential of 6G technology in healthcare, particularly in smart city settings, focusing on its enhanced data capabilities, AI's role in healthcare optimization, infrastructure support, interoperability,...

Race-Performance Parameters Differentiating World-Best From National-Level Swimmers: A Race Video Analysis and Machine-Learning Approach.

International journal of sports physiology and performance
BACKGROUND: Elite swimming performance is determined by a complex interplay of anthropometric, physiological, biomechanical, and technical factors. Previous research highlights how the 100-m freestyle demands explosive power, technical proficiency, a...

The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.

Journal of internal medicine
Healthcare-associated infections (HAIs) are common adverse events, and surveillance is considered a core component of effective HAI reduction programmes. Recently, efforts have focused on automating the traditional manual surveillance process by util...

Neuronal dynamics of slow and fast-motion motor imagery.

Neuroscience
Motor imagery (MI) is a cognitive process requiring mental simulation of physical actions, engaging neural networks that overlap with those activated during actual execution. This study investigated the neural correlates of slow and fast MI in ten he...

Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

Ecotoxicology and environmental safety
BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abnormal glucose metabolism, particularly type 2 diabetes. Hyperglycemia can increase the formation of a...

Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China.

Ecotoxicology and environmental safety
Soil heavy metal contamination poses serious health risks, but few studies have quantitatively assessed disparities in these risks between urban and rural populations. To address this gap, we introduce a novel framework integrating machine learning a...

Long-term exposure to PM and liver cancer mortality: Insights into the role of smaller particulate fractions.

Ecotoxicology and environmental safety
Particulate matter (PM) is a recognized carcinogen, but the effects of PM on liver cancer remain underexplored. This study investigates the long-term association between PM and liver cancer mortality, as well as the contribution of smaller particles ...