AIMC Topic: Retrospective Studies

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CT-based deep learning model for predicting the success of extracorporeal shock wave lithotripsy in treating ureteral stones larger than 1 cm.

Urolithiasis Nov 5, 2024
OBJECTIVES: To develop a deep learning (DL) model based on computed tomography (CT) images to predict the success of extracorporeal shock wave lithotripsy (SWL) treatment for patients with ureteral stones larger than 1 cm.
Middle Aged Deep Learning Treatment Outcome Predictive Value of Tests Ureter Ureteral Calculi Lithotripsy Humans Retrospective Studies Tomography, X-Ray Computed Female Adult Male
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A detailed analysis of game statistics of professional tennis players: An inferential and machine learning approach.

PloS one Nov 5, 2024
Tennis, a widely enjoyed sport, motivates athletes and coaches to optimize training for competitive success. This retrospective predictive study examines anthropometric features and statistics of 1990 tennis players in the 2022 season, using 20,040 d...
Athletic Performance Young Adult Athletes Humans Adult Machine Learning Tennis Retrospective Studies Male Female Adolescent
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Machine learning models for predicting dysphonia following anterior cervical discectomy and fusion: a Swedish Registry Study.

The spine journal : official journal of the North American Spine Society Nov 4, 2024
BACKGROUND: Dysphonia is one of the more common complications following anterior cervical discectomy and fusion (ACDF). ACDF is the gold standard for treating degenerative cervical spine disorders, and identifying high-risk patients is therefore cruc...
Registries Cervical Vertebrae Spinal Fusion Diskectomy Dysphonia Humans Adult Machine Learning Male Retrospective Studies Middle Aged Female Postoperative Complications Sweden Aged
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Automatic 3-dimensional quantification of orthodontically induced root resorption in cone-beam computed tomography images based on deep learning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Nov 4, 2024
INTRODUCTION: Orthodontically induced root resorption (OIRR) is a common and undesirable consequence of orthodontic treatment. Traditionally, studies employ manual methods to conduct 3-dimensional quantitative analysis of OIRR via cone-beam computed ...
Root Resorption Male Image Processing, Computer-Assisted Deep Learning Tooth Movement Techniques Humans Adolescent Orthodontics, Corrective Retrospective Studies Cone-Beam Computed Tomography Tooth Root Female Imaging, Three-Dimensional Cross-Sectional Studies
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Artificial intelligence versus conventional methods for RGP lens fitting in keratoconus.

Contact lens & anterior eye : the journal of the British Contact Lens Association Nov 4, 2024
BACKGROUND: To compare the efficiency of three artificial intelligence (AI) frameworks (Standard Machine Learning (ML), Multi-Layer Perceptron (MLP) and Convolution Neural Networks (CNN)) with a reference method (Mean radius of curvature (K)) to pred...
Retrospective Studies Female Young Adult Adult Cornea Male Middle Aged Adolescent Keratoconus Humans Neural Networks, Computer Artificial Intelligence Corneal Topography Contact Lenses Prosthesis Fitting
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Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

Neurology Nov 4, 2024
BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific eff...
Cross-Sectional Studies Male Aging Middle Aged Deep Learning Longitudinal Studies Magnetic Resonance Imaging Neurodegenerative Diseases Multiple Sclerosis Brain Retrospective Studies Female Adult Humans
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

Journal of the American Heart Association Nov 4, 2024
BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in ...
Female Electrocardiography Male Humans Predictive Value of Tests Ventricular Function, Left Infant Artificial Intelligence Ventricular Dysfunction, Right Stroke Volume Adolescent Algorithms Ventricular Dysfunction, Left Echocardiography Child, Preschool Retrospective Studies Ventricular Function, Right Child
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Prediction of recurrence-free survival and risk factors of sinonasal inverted papilloma after surgery by machine learning models.

European journal of medical research Nov 4, 2024
OBJECTIVES: Our research aims to construct machine learning prediction models to identify patients proned to recurrence after inverted papilloma (IP) surgery and guide their follow-up treatment.
Disease-Free Survival Papilloma, Inverted Paranasal Sinus Neoplasms Adult Retrospective Studies Male Humans Middle Aged Female Machine Learning Neoplasm Recurrence, Local Risk Factors Aged
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Combination of Deep Learning Grad-CAM and Radiomics for Automatic Localization and Diagnosis of Architectural Distortion on DBT.

Academic radiology Nov 3, 2024
RATIONALE AND OBJECTIVES: Detection and diagnosis of architectural distortion (AD) on digital breast tomosynthesis (DBT) is challenging. This study applied artificial intelligence (AI) using deep learning (DL) algorithms to detect AD, followed by rad...
Deep Learning Mammography Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Breast Neoplasms Radiomics Middle Aged Humans Algorithms Retrospective Studies Female Aged Adult
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A Stacked Multimodality Model Based on Functional MRI Features and Deep Learning Radiomics for Predicting the Early Response to Radiotherapy in Nasopharyngeal Carcinoma.

Academic radiology Nov 3, 2024
BACKGROUND: This study aimed to construct and assess a comprehensive model that integrates MRI-derived deep learning radiomics, functional imaging (fMRI), and clinical indicators to predict early efficacy of radiotherapy in nasopharyngeal carcinoma (...
Humans Retrospective Studies Male Middle Aged Deep Learning Treatment Outcome Magnetic Resonance Imaging Female Aged Adult Radiomics Multimodal Imaging Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms
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