AIMC Topic: Adult

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Assessment of simulated snoring sounds with artificial intelligence for the diagnosis of obstructive sleep apnea.

Sleep medicine
BACKGROUND: Performing simulated snoring (SS) is a commonly used method to evaluate the source of snoring in obstructive sleep apnea (OSA). SS sounds is considered as a potential biomarker for OSA. SS sounds can be easily recorded, which is a cost-ef...

Explainable machine learning versus known nomogram for predicting non-sentinel lymph node metastases in breast cancer patients: A comparative study.

Computers in biology and medicine
INTRODUCTION: Axillary lymph node dissection (ALND) is the standard of care for breast cancer patients with positive sentinel lymph nodes (SLN), which are the first lymph nodes that drain the breast. However, many patients with positive SLNs may not ...

Decoding face identity: A reverse-correlation approach using deep learning.

Cognition
Face recognition is crucial for social interactions. Traditional approaches primarily rely on subjective judgment, utilizing a pre-selected set of facial features based on literature or intuition to identify critical facial features for face recognit...

Validation of SynthSeg segmentation performance on CT using paired MRI from radiotherapy patients.

NeuroImage
INTRODUCTION: Manual segmentation of medical images is labor intensive and especially challenging for images with poor contrast or resolution. The presence of disease exacerbates this further, increasing the need for an automated solution. To this ex...

Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment.

Sensors (Basel, Switzerland)
Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipp...

Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.

BMC pregnancy and childbirth
BACKGROUND: Developing a combined artificial intelligence (AI) and ultrasound imaging to provide an accurate, objective, and efficient adjunctive diagnostic approach for fetal heart ventricular septal defects (VSD).

Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.

Scientific reports
This study, for the first time, explores the integration of data science and machine learning for the classification and prediction of coronary artery calcium (CAC) scores. It focuses on tooth loss and patient characteristics as key input features to...

Assessing Yemeni university students' public perceptions toward the use of artificial intelligence in healthcare.

Scientific reports
Artificial intelligence (AI) integration in healthcare has emerged as a transformative force, promising to enhance medical diagnosis, treatment, and overall healthcare delivery. Hence, this study investigates university students' perceptions of using...

Ethical and pedagogical implications of AI in language education: An empirical study at Ha'il University.

Acta psychologica
This study aims to evaluate the role of AI as an educational tool from an ethical and pedagogical perspective as it delves into the perceptions of the teaching community whose resistance to technology integration into conventionally managed classroom...

Prediction of pharmacological response in OCD using machine learning techniques and clinical and neuropsychological variables.

Spanish journal of psychiatry and mental health
INTRODUCTION: Obsessive compulsive disorder is associated with affected executive functioning, including memory, cognitive flexibility, and organizational strategies. As it was reported in previous studies, patients with preserved executive functions...