AIMC Topic: Aged

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Multimodal convolutional neural network-based algorithm for real-time detection and differentiation of malignant and inflammatory biliary strictures in cholangioscopy: a proof-of-concept study (with video).

Gastrointestinal endoscopy Sep 13, 2024
BACKGROUND AND AIMS: Deep learning algorithms gained attention for detection (computer-aided detection [CADe]) of biliary tract cancer in digital single-operator cholangioscopy (dSOC). We developed a multimodal convolutional neural network (CNN) for ...
Diagnosis, Computer-Assisted Deep Learning Convolutional Neural Networks ROC Curve Humans Diagnosis, Differential Aged Neural Networks, Computer Sensitivity and Specificity Algorithms Male Female Middle Aged Constriction, Pathologic Video Recording Bile Duct Neoplasms Proof of Concept Study Cholangiocarcinoma Endoscopy, Digestive System Biliary Tract Neoplasms Cholestasis Cholangitis
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Clinical impact of deep learning-derived intravascular ultrasound characteristics in patients with deferred coronary artery.

International journal of cardiology Sep 13, 2024
Prognostic markers for long-term outcomes are lacking in patients with deferred (nonculprit) coronary artery lesions. This study aimed to identify the morphological criteria for predicting adverse outcomes and validate their clinical impact. Using de...
Deep Learning Humans Follow-Up Studies Female Ultrasonography, Interventional Aged Coronary Vessels Coronary Artery Disease Male Middle Aged
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Automatic generation of diffusion tensor imaging for the lumbar nerve using convolutional neural networks.

Magnetic resonance imaging Sep 13, 2024
【PURPOSE】: Diffusion Tensor Imaging (DTI) with tractography is useful for the functional diagnosis of degenerative lumbar disorders. However, it is not widely used in clinical settings due to time and health care provider costs, as it is performed ma...
Deep Learning Aged Humans Image Processing, Computer-Assisted Adult Lumbosacral Region Neural Networks, Computer Male Diffusion Tensor Imaging Software Middle Aged Female
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Integrating StEP-COMPAC definition and enhanced recovery after surgery status in a machine-learning-based model for postoperative pulmonary complications in laparoscopic hepatectomy.

Anaesthesia, critical care & pain medicine Sep 13, 2024
BACKGROUND: Postoperative pulmonary complications (PPCs) contribute to high mortality rates and impose significant financial burdens. In this study, a machine learning-based prediction model was developed to identify patients at high risk of developi...
Laparoscopy Lung Diseases Humans Adult Machine Learning Hepatectomy Male Retrospective Studies Enhanced Recovery After Surgery Middle Aged Female Postoperative Complications Aged
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Latent Trajectories of Cerebral Perfusion Pressure and Risk Prediction Models Among Patients with Traumatic Brain Injury: Based on an Interpretable Artificial Neural Network.

World neurosurgery Sep 13, 2024
OBJECTIVE: This study aimed to characterize long-term cerebral perfusion pressure (CPP) trajectory in traumatic brain injury (TBI) patients and construct an interpretable prediction model to assess the risk of unfavorable CPP evolution patterns.
Humans Brain Injuries, Traumatic Adult Intracranial Pressure Neural Networks, Computer Male Blood Pressure Middle Aged Algorithms Cerebrovascular Circulation Risk Assessment Female Hospital Mortality Aged
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Predicting invasion in early-stage ground-glass opacity pulmonary adenocarcinoma: a radiomics-based machine learning approach.

BMC medical imaging Sep 13, 2024
BACKGROUND: To design a pulmonary ground-glass nodules (GGN) classification method based on computed tomography (CT) radiomics and machine learning for prediction of invasion in early-stage ground-glass opacity (GGO) pulmonary adenocarcinoma.
Lung Neoplasms Neoplasm Invasiveness Adenocarcinoma of Lung Sensitivity and Specificity Radiomics Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Machine Learning
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Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine.

Journal of imaging informatics in medicine Sep 12, 2024
This study aimed to develop a graph neural network (GNN) for automated three-dimensional (3D) magnetic resonance imaging (MRI) visualization and Pfirrmann grading of intervertebral discs (IVDs), and benchmark it against manual classifications. Lumbar...
Imaging, Three-Dimensional Magnetic Resonance Imaging Lumbar Vertebrae Intervertebral Disc Degeneration Intervertebral Disc Young Adult Adult Male Middle Aged Humans Neural Networks, Computer Retrospective Studies Female Reproducibility of Results Aged
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Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).

Journal of imaging informatics in medicine Sep 12, 2024
The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delineations generated using a convolutional neural network (CNN). One hundred eighty-six CT scans from 48 PM patients were segmented...
Aged Male Middle Aged Convolutional Neural Networks Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Female Mesothelioma Pleural Neoplasms Probability Tumor Burden
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Artificial Intelligence-Based Surgery Support Model Using Intraoperative Radiographs for Assessing the Acetabular Component Angle.

The Journal of arthroplasty Sep 12, 2024
BACKGROUND: This study aimed to develop an artificial intelligence-based surgical support model for assessing the acetabular component angle using intraoperative radiographs during total hip arthroplasty and verify its accuracy.
Male Tomography, X-Ray Computed Humans Middle Aged Surgery, Computer-Assisted Acetabulum Artificial Intelligence Female Arthroplasty, Replacement, Hip Radiography Aged Hip Prosthesis Aged, 80 and over Adult
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Diagnostic Performance of the Offline Medios Artificial Intelligence for Glaucoma Detection in a Rural Tele-Ophthalmology Setting.

Ophthalmology. Glaucoma Sep 12, 2024
PURPOSE: This study assesses the diagnostic efficacy of offline Medios Artificial Intelligence (AI) glaucoma software in a primary eye care setting, using nonmydriatic fundus images from Remidio's Fundus-on-Phone (FOP NM-10). Artificial intelligence ...
Female Aged Cross-Sectional Studies Intraocular Pressure Male Middle Aged Rural Population Visual Acuity Ophthalmology Humans Glaucoma Artificial Intelligence Prospective Studies Telemedicine Visual Fields
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