AIMC Topic: Humans

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Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.

Journal of bone and mineral metabolism
INTRODUCTION: Artificial intelligence (AI)-based systems using chest images are potentially reliable for diagnosing osteoporosis.

Machine learning allows expert level classification of intraoperative motor evoked potentials during neurosurgical procedures.

Computers in biology and medicine
OBJECTIVE: To develop and evaluate machine learning (ML) approaches for muscle identification using intraoperative motor evoked potentials (MEPs), and to compare their performance to human experts.

AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...

TriCAFFNet: A Tri-Cross-Attention Transformer with a Multi-Feature Fusion Network for Facial Expression Recognition.

Sensors (Basel, Switzerland)
In recent years, significant progress has been made in facial expression recognition methods. However, tasks related to facial expression recognition in real environments still require further research. This paper proposes a tri-cross-attention trans...

Preovulatory progesterone levels are the top indicator for ovulation prediction based on machine learning model evaluation: a retrospective study.

Journal of ovarian research
BACKGROUND: Accurately predicting ovulation timing is critical for women undergoing natural cycle-frozen embryo transfer. However, the precise predicting of the ovulation timing remains challenging due to the lack of consensus among different clinics...

Deep learning assisted segmentation of the lumbar intervertebral disc: a systematic review and meta-analysis.

Journal of orthopaedic surgery and research
BACKGROUND: In recent years, deep learning (DL) technology has been increasingly used for the diagnosis and treatment of lumbar intervertebral disc (IVD) degeneration. This study aims to evaluate the performance of DL technology for IVD segmentation ...

The acceptability and effectiveness of artificial intelligence-based chatbot for hypertensive patients in community: protocol for a mixed-methods study.

BMC public health
BACKGROUND: Chatbots can provide immediate assistance tailored to patients' needs, making them suitable for sustained accompanying interventions. Nevertheless, there is currently no evidence regarding their acceptability by hypertensive patients and ...

Automatic prediction of obstructive sleep apnea in patients with temporomandibular disorder based on multidata and machine learning.

Scientific reports
Obstructive sleep apnea (OSA) is closely associated with the development and chronicity of temporomandibular disorder (TMD). Given the intricate pathophysiology of both OSA and TMD, comprehensive diagnostic approaches are crucial. This study aimed to...

Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.

Scientific reports
Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with both therapeutic and diagnostic applications. As accurate coil placement is known to be essential for focal stimulation, computational models have been ...

Clinical audit of an artificial intelligence (AI) empowered smile simulation system: a prospective clinical trial.

Scientific reports
Smile aesthetics is an important factor to consider during orthodontic treatment planning. The aim of the present study is to assess the predictability of Invisalign SmileView for digital AI smile simulation in comparison to actual smile treatment ou...