AIMC Topic: Humans

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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...

PND.heter.cluster: An R package for estimating cluster-specific treatment effects in partially nested designs.

Behavior research methods
Partially nested designs-where clustering occurs in some but not all study arms-are common in psychological and behavioral research. In these designs, clustering often arises in the treatment arm due to the treatment delivery, such as individuals clu...

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...

AI-enhanced bilingual banking assistant.

Scientific reports
Financial literacy and access to banking services are still major challenges, especially in multilingual regions. Many people who do not speak English fluently face difficulties using traditional banking online systems. To help solve this problem, we...

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...

Applying machine learning to predict quality ANC determinants in Bangladesh: a BDHS-2022 cross-sectional study.

Scientific reports
Quality antenatal care (ANC) is critical for maternal and neonatal health. Despite improvements in healthcare, disparities in ANC access and quality persist, particularly in underserved areas of Bangladesh. This study aimed to identify the key determ...

Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...

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...