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Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.

Scientific reports
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...

A new framework for mental illnesses diagnosis using wearable devices aided by improved convolutional neural network.

Scientific reports
Stress inherent in the modern world is considered one of the main causes of Mental Health Disorders (MHDs) that spread in every country around the world. These mental and behavioral problems primarily affect the mind and brain that change emotions an...

Perceptions and Attitudes of Chinese Oncologists Toward Endorsing AI-Driven Chatbots for Health Information Seeking Among Patients with Cancer: Phenomenological Qualitative Study.

Journal of medical Internet research
BACKGROUND: Chatbots driven by large language model artificial intelligence (AI) have emerged as potential tools to enhance health information access for patients with cancer. However, their integration into patient education raises concerns among on...

Innovative Mobile App (CPD By the Minute) for Continuing Professional Development in Medicine: Multimethods Study.

JMIR medical education
BACKGROUND: Many national medical governing bodies encourage physicians to engage in continuing professional development (CPD) activities to cultivate their knowledge and skills to ensure their clinical practice reflects the current standards and evi...

Leveraging stacked classifiers for exploring the role of hedonic processing between major depressive disorder and schizophrenia.

Psychological medicine
BACKGROUND: Anhedonia, a transdiagnostic feature common to both Major Depressive Disorder (MDD) and Schizophrenia (SCZ), is characterized by abnormalities in hedonic experience. Previous studies have used machine learning (ML) algorithms without focu...

Tackling inter-subject variability in smartwatch data using factorization models.

Scientific reports
Smartwatches enable longitudinal and continuous data acquisition. This has the potential to remotely monitor (changes) of the health of users. However, differences among subjects (inter-subject variability) limit a model to generalize to unseen subje...

Development and validation of an improved volumetric breast density estimation model using the ResNet technique.

Biomedical physics & engineering express
. Temporal changes in volumetric breast density (VBD) may serve as prognostic biomarkers for predicting the risk of future breast cancer development. However, accurately measuring VBD from archived x-ray mammograms remains challenging. In a previous ...

Assessing the impact of information on patient attitudes toward artificial intelligence-based clinical decision support (AI/CDS): a pilot web-based SMART vignette study.

Journal of medical ethics
BACKGROUND: It is increasingly recognised that the success of artificial intelligence-based clinical decision support (AI/CDS) tools will depend on physician and patient trust, but factors impacting patients' views on clinical care reliant on AI have...

An autoencoder learning method for predicting breast cancer subtypes.

PloS one
Heterogeneity of breast cancer poses several challenges for detection and treatment. With next-generation sequencing, we can now map the transcriptional profile of each patient's breast tissue, which has the potential for identifying and characterizi...

Factors influencing the performance of cardiopulmonary resuscitation by lay rescuers: A qualitative study based on the Theory of Planned Behavior.

PloS one
AIMS: This study investigated the underlying causes for the current low rate of cardiopulmonary resuscitation (CPR) implementation among lay rescuers. Specifically, the study aimed to identify the factors that influence both the intention to perform ...