AI Medical Compendium Topic:
Adult

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Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

The journal of headache and pain
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...

The analysis of optimization in music aesthetic education under artificial intelligence.

Scientific reports
In the artificial intelligence (AI) domain, effectively integrating deep learning (DL) technology with the content, teaching methodologies, and learning processes of music aesthetic education remains a subject worthy of in-depth exploration and discu...

A muscle synergy-based method to improve robot-assisted movements.

Scientific reports
There is increasing interest in using assistive robotic devices to support motor re-learning and recovery in individuals with neurological impairments. These robots aim to enhance overall motor control by providing adaptive assistance. However, using...

Deep learning prediction of mammographic breast density using screening data.

Scientific reports
This study investigated a series of deep learning (DL) models for the objective assessment of four categories of mammographic breast density (e.g., fatty, scattered, heterogeneously dense, and extremely dense). A retrospective analysis was conducted ...

Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI)-enabled decision support systems are critical tools in medical practice; however, their reliability is not absolute, necessitating human oversight for final decision-making. Human reliance on such systems can ...

Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG.

JMIR formative research
BACKGROUND: Template-based automatic item generation (AIG) is more efficient than traditional item writing but it still heavily relies on expert effort in model development. While nontemplate-based AIG, leveraging artificial intelligence (AI), offers...

Greenspace and depression incidence in the US-based nationwide Nurses' Health Study II: A deep learning analysis of street-view imagery.

Environment international
BACKGROUND: Greenspace exposure is associated with lower depression risk. However, most studies have measured greenspace exposure using satellite-based vegetation indices, leading to potential exposure misclassification and limited policy relevance. ...

Leveraging Artificial Intelligence to Uncover Symptom Burden in Palliative Care: Analysis of Nonscheduled Visits Using a Phi-3 Small Language Model.

JCO global oncology
PURPOSE: This study aimed to differentiate nonscheduled visits (NSVs) in an outpatient palliative care setting that are driven by or accompanied by uncontrolled symptoms from those that are administrative or routine, such as prescription refills and ...

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.

JCO clinical cancer informatics
PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinical decision making and tailoring treatment. Despite the significant success of targeted therapy and immunotherapy in advanced melanoma, substantial var...

A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.

Neuroradiology
PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was dev...