AIMC Topic: Male

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Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity.

BMC cardiovascular disorders
BACKGROUND: Obesity is a disease with high heterogeneity. Both overall obesity and central obesity are associated with increased risks of having cardio-metabolic co-morbidities. This study is aimed to examine the cardio-metabolic characteristics and ...

Automated detection of mouth opening in newborn infants.

Behavior research methods
Automated behavioral measurement using machine learning is gaining ground in psychological research. Automated approaches have the potential to reduce the labor and time associated with manual behavioral coding, and to enhance measurement objectivity...

Decoding covert visual attention of electroencephalography signals using continuous wavelet transform and deep learning approach.

Scientific reports
Covert visual attention decoding from EEG signals is a key challenge in cognitive neuroscience and brain-computer interface applications. Traditional approaches often rely on manual feature extraction and handcrafted pipelines, which limit scalabilit...

Distinguishing acute and chronic TMD in adolescent patients.

Scientific reports
This retrospective cross-sectional study aimed to elucidate the clinical and imaging characteristics of chronic temporomandibular disorder (TMD) compared to acute TMD in adolescents, and to identify factors associated with symptom chronicity. The stu...

Enhancing the precision of male fertility diagnostics through bio inspired optimization techniques.

Scientific reports
Infertility is a growing concern in today's technologically driven and mechanized world, with male related factors contributing to nearly half of all cases yet often remaining under diagnosed due to societal misconceptions and stigma. Prolonged seden...

Intelligent monitoring system for quality of life of colostomy patients based on deep learning and AR.

Scientific reports
The clinical challenges in monitoring high-incidence complications in patients with colostomy after colorectal cancer surgery have led to the development of an intelligent monitoring system based on deep learning and augmented reality technology in t...

Using multiple machine learning algorithms to predict spinal cord injury in patients with cervical spondylosis: a multicenter study.

Scientific reports
Degenerative cervical spondylosis, a chronic and progressive condition, has a considerable impact on global health. Spinal cord injury, a severe sequela of this disease, can result from this disease. Machine learning (ML) has emerged as a valuable to...

Primary teachers' acceptance and sustained adoption of AI powered learner corpora for writing instruction through TAM and ECM perspectives.

Scientific reports
Artificial intelligence (AI) offers significant potential to enhance writing instruction in primary education. However, its sustained adoption by English language teachers remains insufficiently understood. This study examines the factors influencing...

Inter-machine harmonization of multicenter echocardiographic images for improvement of left ventricular ejection fraction prediction model.

Scientific reports
One of the common challenges in medical artificial intelligence (AI) applications using echocardiography is the lack of image data harmonization. This study aims to improve the prediction accuracy of left ventricular ejection fraction (LVEF) AI model...

The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis.

Nature communications
Lyme neuroborreliosis (LNB), a nervous system infection caused by tick-borne spirochetes of the Borrelia burgdorferi sensu lato complex, is among the most frequent bacterial infections of the nervous system in Europe. Early diagnosis and continuous m...