AIMC Topic: Artificial Intelligence

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Using a coloring activity to identify children's development of visual-motor integration: an application of artificial intelligence.

Annals of medicine
AIM: Visual-motor integration (VMI) is an important indicator in children with learning disabilities. We aimed to use performance in a coloring activity to identify children's VMI developmental status.

DPDispatcher: Scalable HPC Task Scheduling for AI-Driven Science.

Journal of chemical information and modeling
Artificial intelligence (AI) is reshaping computational science, but AI-driven workflows routinely span heterogeneous tasks executed across diverse high-performance computing (HPC) systems. We introduce DPDispatcher, an open-source Python framework f...

Evaluating the performance of five large language models in answering Delphi consensus questions relating to patellar instability and medial patellofemoral ligament reconstruction.

BMC musculoskeletal disorders
PURPOSE: Artificial intelligence (AI) has become incredibly popular over the past several years, with large language models (LLMs) offering the possibility of revolutionizing the way healthcare information is shared with patients. However, to prevent...

Performance of artificial intelligence-assisted ultrasound elastography in classifying benign and malignant breast tumors: a systematic review and meta-analysis.

BMC medical imaging
BACKGROUND: Precise benign and malignant breast tumors classification is essential for effective treatment planning and outcome prognostication. Medical imaging's capability to classify breast tumors has been greatly improved by the accelerated advan...

Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis.

Scientific reports
Male pattern hair loss (MPHL) is a common dermatological condition with significant psychological and clinical impacts. Traditional grading systems, such as the Norwood-Hamilton and Basic and Specific (BASP) classifications, rely on subjective assess...

Smartphone-based biosensing: a review of optical imaging, microfluidic integration, and AI-enhanced analysis.

Mikrochimica acta
Recently, the integration of smartphone-based platforms into biomedical sensing has provided portable, low-cost, and scalable alternatives to conventional laboratory diagnostics. According to the advances in mobile imaging, embedded sensors, microflu...

A cross sectional feasibility study to evaluate the usability and efficacy of Swaasa AI platform for rapid respiratory health assessment.

Scientific reports
Analysing cough sounds is vital in pulmonary medicine. Recently, AI tools are being trained to analyse the acoustic signals of cough sounds so that more cases can be quickly tested, thereby reducing the patient load on primary healthcare systems. In ...

Explainable artificial intelligence for predictive modeling of student stress in higher education.

Scientific reports
Student stress in higher education remains a pervasive problem, yet many institutions lack affordable, scalable, and interpretable tools for its detection and management. Existing methods frequently depend on costly physiological sensors and opaque m...

AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer.

Nature communications
Risk stratification remains a critical challenge in non-small cell lung cancer patients for optimal therapy selection. In this study, we develop an artificial intelligence-powered spatial cellomics approach that combines histology, multiplex immunofl...

Quality Assessment of Large Language Model-Generated Medical Dialogue for Clinical Vignettes: Evaluation Study.

JMIR formative research
BACKGROUND: Traditional clinical vignettes, though widely used in medical education, often focus on prototypical presentations; require substantial time and effort to develop; and fail to represent patient diversity, the complexity of clinical condit...