AIMC Topic: Adult

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Prediction Trough Concentrations of Valproic Acid Among Chinese Adult Patients with Epilepsy Using Machine Learning Techniques.

Pharmaceutical research
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict Valproic acid (VPA) trough concentrations in Chinese adult epilepsy patients.

Identifying Neuro-Inflammatory Biomarkers of Generalized Anxiety Disorder from Lymphocyte Subsets Based on Machine Learning Approaches.

Neuropsychobiology
INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of generalized anxiety disorder (GAD). The purpose of this study was to identify and characterize inflammatory biomarkers in the diagnosis of GAD based on ma...

Reliability of artificial intelligence-driven markerless motion capture in gait analyses of healthy adults.

PloS one
The KinaTrax markerless motion capture system, used extensively in the analysis of baseball pitching and hitting, is currently being adapted for use in clinical biomechanics. In clinical and laboratory environments, repeatability is inherent to the q...

Gender-Equity Model for Liver Allocation Using Artificial Intelligence (GEMA-AI) for Waiting List Liver Transplant Prioritization.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND & AIMS: We aimed to develop and validate an artificial intelligence score (gender-equity model for liver allocation using artificial intelligence [GEMA-AI]) to predict liver transplantation (LT) waiting list outcomes using the same input v...

Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

Journal of hepatology
BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of focal liver lesions (FLLs). Ultrasound is the most common imaging examination but lacks accuracy. Contrast-enhanced ultrasound (CEUS) offers better perfo...

Improved Image Quality Through Deep Learning Acceleration of Gradient-Echo Acquisitions in Uterine MRI: First Application with the Female Pelvis.

Academic radiology
RATIONALE AND OBJECTIVES: The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus.

Development and application of a machine learning-based antenatal depression prediction model.

Journal of affective disorders
BACKGROUND: Antenatal depression (AND), occurring during pregnancy, is associated with severe outcomes. However, there is a lack of objective and universally applicable prediction methods for AND in clinical practice. We leveraged sociodemographic an...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Computers in biology and medicine
Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we...

National survey on data governance and digital surgery: Challenges and opportunities for surgeons in the era of artificial intelligence.

Cirugia espanola
INTRODUCTION: This study evaluates the knowledge of Spanish surgeons regarding data governance and Digital Surgery, their usage, errors, and training deficiencies, as well as differences in knowledge between those who perform robotic surgery and thos...