AIMC Topic: Female

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Artificial intelligence-based detection of atrial fibrillation from chest radiographs.

European radiology
OBJECTIVE: The purpose of this study was to develop an artificial intelligence (AI)-based model to detect features of atrial fibrillation (AF) on chest radiographs.

Automated Facial Expression Recognition Framework Using Deep Learning.

Journal of healthcare engineering
Facial expression is one of the most significant elements which can tell us about the mental state of any person. A human can convey approximately 55% of information nonverbally and the remaining almost 45% through verbal communication. Automatic fac...

Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries.

Journal of healthcare engineering
BACKGROUND: Dental caries is one of the major oral health problems and is increasing rapidly among people of every age (children, men, and women). Deep learning, a field of Artificial Intelligence (AI), is a growing field nowadays and is commonly use...

Development of an affordable, immersive model for robotic vaginal cuff closure: a randomized trial.

Journal of robotic surgery
Safe and secure closure of the vaginal cuff is a critical component of a robotic assisted hysterectomy procedure. Our aim in this study is to develop and validate a novel vaginal cuff closure model (VC) created from porcine heart that allows trainees...

Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.

Medical physics
BACKGROUND: Digital breast tomosynthesis (DBT) is a technique that can overcome the shortcomings of conventional X-ray mammography and can be effective for the early screening of breast cancer. The compression of the breast is essential during the DB...

Categorized contrast enhanced mammography dataset for diagnostic and artificial intelligence research.

Scientific data
Contrast-enhanced spectral mammography (CESM) is a relatively recent imaging modality with increased diagnostic accuracy compared to digital mammography (DM). New deep learning (DL) models were developed that have accuracies equal to that of an avera...

Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes.

European radiology
OBJECTIVES: To investigate whether deep learning reconstruction (DLR) provides improved cervical spine MR images using a 1.5 T unit in the evaluation of degenerative changes without increasing imaging time.

Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.

Radiology
Background Artificial intelligence (AI) has shown promising results for cancer detection with mammographic screening. However, evidence related to the use of AI in real screening settings remain sparse. Purpose To compare the performance of a commerc...