AI Medical Compendium

Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models.

Scientific reports Jul 17, 2026

The prediction and recognition of unstable human walking patterns are of high importance for active video surveillance, smart environments, and assistive healthcare, particularly for fall detection in the elderly. This research investigates the utili... read more

Breast cancer detection and classification via a robust deep learning approach.

Scientific reports Jul 17, 2026

This work presents a leakage-controlled deep-learning framework for breast cancer classification using the CBIS-DDSM mammography archive. The proposed pipeline combines patient-level data partitioning before augmentation, a two-stage transfer-learnin... read more

HEC-NAS-FDS: hybrid expert-conditioned exhaustive neural network architecture search over finite design space.

Scientific reports Jul 17, 2026

This article presents a new proof-of-concept method called Hybrid Expert-Conditioned Exhaustive Neural Network Architecture Search over Finite Design Space (HEC-NAS-FDS), which aims to find a suitable deep neural network (DNN) architecture with lower... read more

Physics-constrained machine-learning surrogates for the colebrook friction factor: monotonic gradient boosting, uncertainty quantification, and open benchmarking.

Scientific reports Jul 17, 2026

The Darcy-Weisbach friction factor is used to determine the head losses occurring due to friction in pressurised pipes. It is defined by the Colebrook-White Equation as an implicit function of the Reynolds number and relative roughness for which iter... read more

Evaluation of the performance and temporal variability of large language models in patient education regarding pneumothorax: a seven-day analysis.

Scientific reports Jul 17, 2026

This study investigates the readability, clinical reliability, and temporal consistency of artificial intelligence (AI) chatbots regarding pneumothorax information. A question bank comprising 40 patient-centered queries was deployed across three larg... read more

Cross-cultural adaptation and psychometric evaluation of the Japanese version of the scale for the assessment of non-experts' AI literacy among medical trainees in a multicenter cross-sectional study.

Scientific reports Jul 17, 2026

This cross-sectional study aimed to develop the Japanese version of the "Scale for the assessment of non-experts' AI literacy" (J-SNAIL) and provide its initial psychometric evidence. In 2025, after translating the SNAIL into Japanese according to an... read more

Artificial intelligence needs better health systems to reduce inequalities.

NPJ digital medicine Jul 17, 2026

Artificial Intelligence (AI) technologies are increasingly prevalent in healthcare, yet without adaptive governance, even well-designed systems risk exacerbating health inequalities. This perspective examines five interconnected governance domains: l... read more

A lightweight deep learning model for real-time in-vehicle driver distraction detection with low-latency inference.

Scientific reports Jul 17, 2026

Driver distraction is a major road-safety concern that requires reliable and efficient in-vehicle monitoring systems. The main contribution of this work is a reproducible driver-disjoint and deployment-oriented evaluation framework that jointly exami... read more

Deep Reinforcement Learning-based combat recognition of traditional Chinese Sanda under artificial intelligence technology.

Scientific reports Jul 17, 2026

In the modern sports ecosystem, the digital preservation of traditional Chinese Sanda requires precise methodology to capture its complex technical lineage. This study proposes an innovative combat recognition framework for traditional Chinese Sanda ... read more

A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions.

Scientific reports Jul 17, 2026

Malaria remains a major global health burden, particularly in low-resource regions where microscopic diagnosis relies heavily on expert interpretation and is prone to variability. Although deep learning models have demonstrated strong classification ... read more

Artificial Intelligence Medical Compendium

Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models.

Breast cancer detection and classification via a robust deep learning approach.

HEC-NAS-FDS: hybrid expert-conditioned exhaustive neural network architecture search over finite design space.

Physics-constrained machine-learning surrogates for the colebrook friction factor: monotonic gradient boosting, uncertainty quantification, and open benchmarking.

Evaluation of the performance and temporal variability of large language models in patient education regarding pneumothorax: a seven-day analysis.

Cross-cultural adaptation and psychometric evaluation of the Japanese version of the scale for the assessment of non-experts' AI literacy among medical trainees in a multicenter cross-sectional study.

Artificial intelligence needs better health systems to reduce inequalities.

A lightweight deep learning model for real-time in-vehicle driver distraction detection with low-latency inference.

Deep Reinforcement Learning-based combat recognition of traditional Chinese Sanda under artificial intelligence technology.

A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions.

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