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A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.

Scientific reports
Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social communication and repetitive or obsessive behaviors. Early detection of autism is crucial, as it allows t...

Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.

Translational psychiatry
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...

Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study.

Journal of medical Internet research
BACKGROUND: Qualitative research is crucial for understanding the values and beliefs underlying individual experiences, emotions, and behaviors, particularly in social sciences and health care. Traditionally reliant on manual analysis by experienced ...

A robotic rehabilitation intervention in a home setting during the Covid-19 outbreak: a feasibility pilot study in patients with stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Telerehabilitation allows patients to engage in therapy away from healthcare facilities, often in the comfort of their homes. Studies have suggested that it can effectively improve motor and cognitive function. However, its applicability ...

Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.

Frontiers in endocrinology
BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that typically requires a standardized oral glucose tolerance test (OGTT) for diagnosis. This study aims to predict glucose tolerance status in Chinese Ha...

Personalized therapeutic strategies and prognosis for advanced laryngeal squamous cell carcinoma: Insights from machine learning models.

American journal of otolaryngology
PURPOSE: Despite the development of diverse treatment options, there has been an increase in mortality rates for laryngeal squamous cell carcinoma (LSCC). Our research employed survival analysis and machine learning (ML) techniques to evaluate the im...

Single Joint Hybrid Assistive Limb (HAL-SJ) robotic exoskeleton therapy in improving functional outcomes among workers with wrist fractures: Study protocol for a randomized controlled trial.

PloS one
INTRODUCTION: Robotic technologies have been developed for motor rehabilitation and such robots have shown favourable results when compared with equivalent doses of usual clinical therapy. Recently, robotic interventions have been suggested to be app...

New perspective: An in vitro study on inferring the post-mortem interval (PMI) of human skeletal muscle based on ATR-FTIR spectroscopy combined with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The determination of the PMI remains one of the most critical challenges within the field of forensic science. Nonetheless, the estimation of PMI has emerged as one of the most complex and challenging domains of research within the field, primarily d...

Prediction of Lymphoma Aggressiveness Using Machine Learning Algorithms.

International journal of laboratory hematology
INTRODUCTION: Lymph nodes are essential to diagnose lymphoid neoplasms, metastases, and infections. Some lymphomas, particularly aggressive non-Hodgkin lymphomas (NHL), need urgent diagnosis. Combining lymph node cytology (LNC) and flow cytometry (FC...