AIMC Topic: Adult

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Machine learning can reliably predict malignancy of breast lesions based on clinical and ultrasonographic features.

Breast cancer research and treatment
PURPOSE: To establish a reliable machine learning model to predict malignancy in breast lesions identified by ultrasound (US) and optimize the negative predictive value to minimize unnecessary biopsies.

The impact of AI-based decision support systems on nursing workflows in critical care units.

International nursing review
AIM: This research examines the effects of artificial intelligence (AI)-based decision support systems (DSS) on the operational processes of nurses in critical care units (CCU) located in Amman, Jordan.

Enhanced neuroplasticity and gait recovery in stroke patients: a comparative analysis of active and passive robotic training modes.

BMC neurology
BACKGROUND: Stroke is a leading cause of long-term disability, with lower limb dysfunction being a common sequela that significantly impacts patients' mobility and quality of life. Robotic-assisted training has emerged as a promising intervention for...

Identifying the key factors of mercury exposure in residents of southwestern Iran using machine learning algorithms.

Environmental geochemistry and health
It is necessary to predict hair mercury (Hg) levels and specify the related effective factors to develop preventive strategies to reduce Hg exposure in different regions. This study is the first effort to investigate the effectiveness of eight machin...

Applying machine learning with MobileNetV2 model for rapid screening of vaginal discharge samples in vaginitis diagnosis.

Scientific reports
Vaginitis is a prevalent gynecological condition that impacts women's quality of life, with most women likely to experience it at least once. Traditional diagnosis involves manually observing vaginal discharge samples under a microscope. This process...

Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT.

BMC medical imaging
PURPOSE: To compare the image quality and pulmonary nodule detectability and measurement accuracy between deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) of chest ultra-low-dose CT (ULDCT).

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety.

BMC pregnancy and childbirth
BACKGROUND: Artificial intelligence (AI) is increasingly used in healthcare interventions to provide accessible, continuous, and personalized patient support. This study investigates the impact of a mobile breastfeeding counseling application develop...

Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading.

BMC medical informatics and decision making
PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas.

Automated diagnosis for extraction difficulty of maxillary and mandibular third molars and post-extraction complications using deep learning.

Scientific reports
Optimal surgical methods require accurate prediction of extraction difficulty and complications. Although various automated methods related to third molar (M3) extraction have been proposed, none fully predict both extraction difficulty and post-extr...

Early efficacy observation of suspended lower-limb rehabilitation robot-assisted therapy in patients with intensive care unit-acquired weakness: a study protocol for a self-controlled randomised controlled trial.

BMJ open
INTRODUCTION: Intensive care unit-acquired weakness (ICUAW) is a common and severe complication in critically ill patients, associated with high morbidity and poor prognosis. Despite increasing focus on ICUAW, definitive diagnostic and therapeutic st...