AIMC Topic: Humans

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Effectiveness of a Machine Learning-Enabled Skincare Recommendation for Mild-to-Moderate Acne Vulgaris: 8-Week Evaluator-Blinded Randomized Controlled Trial.

JMIR dermatology
BACKGROUND: Acne vulgaris (AV) is one of the most common skin disorders, with a peak incidence in adolescence and early adulthood. Topical treatments are usually used for mild to moderate AV; however, a lack of adherence to topical treatment is seen ...

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Wearable devices are increasingly used for monitoring health and detecting digital biomarkers related to chronic diseases such as metabolic syndrome (MetS). Although circadian rhythm disturbances are known to contribute to MetS, few studi...

A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation.

JMIR medical informatics
BACKGROUND: Syndrome differentiation in traditional Chinese medicine (TCM) is an ancient principle that guides disease diagnosis and treatment. Among these, the cold and hot syndromes play a crucial role in identifying the nature of the disease and g...

Equalizing access: How robotics and AI can transform surgical care worldwide.

Science robotics
The integration of robotics and artificial intelligence holds promise for improving access to surgical care worldwide.

Surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery.

Science robotics
Surgical robots capable of autonomously performing various tasks could enhance efficiency and augment human productivity in addressing clinical needs. Although current solutions have automated specific actions within defined contexts, they are challe...

Specific Contribution of the Cerebellar Inferior Posterior Lobe to Motor Learning in Degenerative Cerebellar Ataxia.

Cerebellum (London, England)
BACKGROUND AND OBJECTIVE: Degenerative cerebellar ataxia, a group of progressive neurodegenerative disorders, is characterised by cerebellar atrophy and impaired motor learning. Using CerebNet, a deep learning algorithm for cerebellar segmentation, t...

Integrated machine learning and deep learning-based virtual screening framework identifies novel natural GSK-3β inhibitors for Alzheimer's disease.

Journal of computer-aided molecular design
Alzheimer's disease (AD) is a progressive neurodegenerative disorder lacking effective therapies. Glycogen synthase kinase-3β (GSK-3β), a key regulator of Aβ aggregation and Tau hyperphosphorylation, has emerged as a promising therapeutic target. Her...

AI-driven scientometric analysis with recency insights: lower urinary tract symptoms in older and frail populations.

World journal of urology
PURPOSE: This artificial intelligence (AI)-driven scientometric analysis, conducted using the Mynd discovery platform, explores research trends in lower urinary tract symptoms (LUTS) among older patients. By applying its novel recency metric, the stu...

Unicorns transforming the practice of urology: value creation and allocation in the digital age.

World journal of urology
PURPOSE: To analyze what kind of products and services unicorns, which create a substantial financial value, provide in urology and what this means for the future of urological practice. So far, the added value of unicorns has hardly been utilised fo...

Automated multi-model framework for malaria detection using deep learning and feature fusion.

Scientific reports
Malaria remains a critical global health challenge, particularly in tropical and subtropical regions. While traditional methods for diagnosis are effective, they face some limitations related to accuracy, time consumption, and manual effort. This stu...