AIMC Topic: Female

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Machine learning models for predicting malnutrition in NICU patients: A comprehensive benchmarking study.

Computers in biology and medicine
Malnutrition, affecting both adults and children globally, results from inadequate nutrient intake or loss of body mass. Traditional screening tools, reliant on detailed questionnaires, are costly, time-consuming, and often lack accuracy and generali...

Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...

AI-AIDED VOLUMETRIC ROOT RESORPTION ASSESSMENT FOLLOWING PERSONALIZED FORCES IN ORTHODONTICS: PRELIMINARY RESULTS OF A RANDOMIZED CLINICAL TRIAL.

The journal of evidence-based dental practice
INTRODUCTION: External apical root resorption (EARR) is an undesirable loss of hard tissues of the tooth root frequently affecting to the maxillary incisors. The magnitude of orthodontic forces is a major treatment-related factor associated with EARR...

Passive ankle and hindfoot kinematics within a robot-driven tibial movement envelope.

Journal of biomechanics
Accurate description of individual bone kinematics is essential for understanding individual foot and ankle joint function and interactions. While invasive and noninvasive techniques, including robotic simulators, have advanced the direct measurement...

An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) provides the spatial distribution of magnetic susceptibility within tissues through sequential steps: phase unwrapping and echo combination, mask generation, background field removal, and dipole inversion. Ac...

Oral cavity carcinoma detection using BAT algorithm-optimized machine learning models with transfer learning and random sampling.

Computers in biology and medicine
BACKGROUND: Oral cavity carcinoma remains a major public health concern, where early and accurate detection is vital for improving patient outcomes and survival rates. Current diagnostic systems often face challenges such as limited feature selection...

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Computers in biology and medicine
Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limita...

Effects of an artificial intelligence-based exercise program on pain intensity and disability in patients with neck pain compared with group exercise therapy: A cohort study.

Journal of bodywork and movement therapies
OBJECTIVES: This study compares the effects of an artificial intelligence app-based exercise program with group exercise therapy on pain intensity and neck-related disability in patients with neck pain.

Artificial intelligence in fetal brain imaging: Advancements, challenges, and multimodal approaches for biometric and structural analysis.

Computers in biology and medicine
Artificial intelligence (AI) is transforming fetal brain imaging by addressing key challenges in diagnostic accuracy, efficiency, and data integration in prenatal care. This review explores AI's application in enhancing fetal brain imaging through ul...