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A skin-interfaced wireless wearable device and data analytics approach for sleep-stage and disorder detection.

Proceedings of the National Academy of Sciences of the United States of America
Accurate identification of sleep stages and disorders is crucial for maintaining health, preventing chronic conditions, and improving diagnosis and treatment. Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or fi...

How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.

BMC psychology
INTRODUCTION: Artificial Intelligence (AI) has become part of our everyday lives and is also increasingly applied in psychosocial healthcare as it can enhance it, make it more accessible, and reduce barriers for help seeking. User behaviour and readi...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

BMC medical informatics and decision making
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...

Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: While triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune checkpoint inhibitors, is widely used in the treatment of large hepatocellular carcinoma (HCC), there are...

Mandibular condyle detection using deep learning and double attractor-based energy valley optimizer algorithm.

BMC oral health
The temporomandibular joint (TMJ) constitutes a bilateral ginglymoarthrodial joint, wherein each condyle interacts with its corresponding glenoid fossa of the temporal bone. There is a critical need to understand better and accurately characterize th...

AI for mental health: clinician expectations and priorities in computational psychiatry.

BMC psychiatry
Mental disorders represent a major global health challenge, with an estimated lifetime prevalence approaching 30%. Despite the availability of effective treatments, access to mental health care remains inadequate. Computational psychiatry, leveraging...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Scientific reports
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...

The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.

Scientific reports
To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics models for non-massive breast cancer in dense breast backgrounds. Manual segmentation of ultrasound image...

UANV: UNet-based attention network for thoracolumbar vertebral compression fracture angle measurement.

Scientific reports
Kyphosis is a prevalent spinal condition where the spine curves in the sagittal plane, resulting in spine deformities. Curvature estimation provides a powerful index to assess the deformation severity of scoliosis. In current clinical diagnosis, the ...

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome.

Scientific reports
Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients' quality of life, primarily due to impaired motor function and gait instability. Although conventional neurol...