AIMC Topic: Female

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Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity.

The bone & joint journal
AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction...

Artificial intelligence-assisted precise preoperative prediction of lateral cervical lymph nodes metastasis in papillary thyroid carcinoma via a clinical-CT radiomic combined model.

International journal of surgery (London, England)
OBJECTIVES: This study aimed to develop an artificial intelligence-assisted model for the preoperative prediction of lateral cervical lymph node metastasis (LCLNM) in papillary thyroid carcinoma (PTC) using computed tomography (CT) radiomics, providi...

Clinical value of aortic arch morphology in transfemoral TAVR: artificial intelligence evaluation.

International journal of surgery (London, England)
BACKGROUND: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study w...

Metastatic Lung Lesion Changes in Follow-up Chest CT: The Advantage of Deep Learning Simultaneous Analysis of Prior and Current Scans With SimU-Net.

Journal of thoracic imaging
PURPOSE: Radiological follow-up of oncology patients requires the detection of metastatic lung lesions and the quantitative analysis of their changes in longitudinal imaging studies. Our aim was to evaluate SimU-Net, a novel deep learning method for ...

Artificial intelligence based semi-automatic segmentation for orbital tumor preoperative modeling.

Orbit (Amsterdam, Netherlands)
PURPOSE: With the increasing utilization of endoscopic approaches for primary benign orbital tumor (PBOT) surgery, otolaryngologists and ophthalmologists are challenged with determining candidacy for endoscopic resection based on preoperative imaging...

Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.

Neural networks : the official journal of the International Neural Network Society
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...

Rehabilitation of a Terminal Dentition Patient Using an Immediate Loading Protocol With a Virtual Patient-Assisted Workflow: A Case Report.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
OBJECTIVES: To demonstrate the implementation of a digital workflow for the rehabilitation of a terminal dentition patient with complete-arch implant-supported prostheses.

Segmentation of the nasopalatine canal and detection of canal furcation status with artificial intelligence on cone-beam computed tomography images.

Oral radiology
OBJECTIVES: The nasopalatine canal (NPC) is an anatomical formation with varying morphology. NPC can be visualized using the cone-beam computed tomography (CBCT). Also, CBCT has been used in many studies on artificial intelligence (AI). The "You only...

Deep Learning-Assisted Diagnosis of Malignant Cerebral Edema Following Endovascular Thrombectomy.

Academic radiology
BACKGROUND: Malignant cerebral edema (MCE) is a significant complication following endovascular thrombectomy (EVT) in the treatment of acute ischemic stroke. This study aimed to develop and validate a deep learning-assisted diagnosis model based on t...