AIMC Topic: Retrospective Studies

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Machine learning to predict lymph node metastasis in T1 esophageal squamous cell carcinoma: a multicenter study.

International journal of surgery (London, England) Dec 1, 2024
BACKGROUND: Existing models do poorly when it comes to quantifying the risk of lymph node metastases (LNM). This study aimed to develop a machine-learning model for LNM in patients with T1 esophageal squamous cell carcinoma (ESCC).
Humans Machine Learning Retrospective Studies Female Aged Male Middle Aged Lymphatic Metastasis Esophageal Neoplasms Esophageal Squamous Cell Carcinoma
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Development and validation of a deep learning model for predicting gastric cancer recurrence based on CT imaging: a multicenter study.

International journal of surgery (London, England) Dec 1, 2024
INTRODUCTION: The postoperative recurrence of gastric cancer (GC) has a significant impact on the overall prognosis of patients. Therefore, accurately predicting the postoperative recurrence of GC is crucial.
Middle Aged Deep Learning Neoplasm Recurrence, Local Gastrectomy Humans Female Prognosis Aged Retrospective Studies Adult Tomography, X-Ray Computed Stomach Neoplasms Male
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External validation of the performance of commercially available deep-learning-based lung nodule detection on low-dose CT images for lung cancer screening in Japan.

Japanese journal of radiology Nov 30, 2024
PURPOSE: Artificial intelligence (AI) algorithms for lung nodule detection have been developed to assist radiologists. However, external validation of its performance on low-dose CT (LDCT) images is insufficient. We examined the performance of the co...
Middle Aged Lung Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Solitary Pulmonary Nodule Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Japan Radiation Dosage Female Aged Aged, 80 and over Sensitivity and Specificity Male Humans Retrospective Studies Tomography, X-Ray Computed
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Using machine learning models for predicting monthly iPTH levels in hemodialysis patients.

Computer methods and programs in biomedicine Nov 30, 2024
BACKGROUND AND OBJECTIVE: Intact parathyroid hormone (iPTH), also known as active parathyroid hormone, is an important indicator commonly for monitoring secondary hyperparathyroidism (SHPT) in patients undergoing hemodialysis. The aim of this study w...
Predictive Value of Tests Risk Assessment Registries Humans Renal Dialysis Time Factors Parathyroid Hormone Taiwan Hyperparathyroidism, Secondary Machine Learning Retrospective Studies Female Male
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Predicting sinonasal inverted papilloma attachment using machine learning: Current lessons and future directions.

American journal of otolaryngology Nov 30, 2024
BACKGROUND: Hyperostosis is a common radiographic feature of inverted papilloma (IP) tumor origin on computed tomography (CT). Herein, we developed a machine learning (ML) model capable of analyzing CT images and identifying IP attachment sites.
Male Tomography, X-Ray Computed Humans Middle Aged Female Machine Learning Papilloma, Inverted Algorithms Paranasal Sinus Neoplasms Aged Retrospective Studies Adult
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Machine learning is better than surgeons at assessing unicompartmental knee replacement radiographs.

The Knee Nov 30, 2024
BACKGROUND: Poor results occasionally occur after unicompartmental knee replacement (UKR). It is often difficult, even for experienced surgeons, to determine why patients have poor outcomes from radiographs. The aim was to compare the ability of expe...
Osteoarthritis, Knee Humans Male Middle Aged Radiography Knee Joint Machine Learning Arthroplasty, Replacement, Knee Retrospective Studies Female Aged
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Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.

European radiology Nov 29, 2024
PURPOSE: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.
Humans Retrospective Studies Tomography, X-Ray Computed Female Risk Factors Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Propensity Score Neoplasms, Radiation-Induced Aged Adult Male Middle Aged
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Development and Validation of a Machine Learning Radiomics Model based on Multiparametric MRI for Predicting Progesterone Receptor Expression in Meningioma: A Multicenter Study.

Academic radiology Nov 29, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a machine learning-based prediction model for preoperatively predicting progesterone receptor (PR) expression in meningioma patients using multiparametric magnetic resonance imaging (...
Male Middle Aged Magnetic Resonance Imaging Receptors, Progesterone Meningioma Meningeal Neoplasms Multiparametric Magnetic Resonance Imaging Retrospective Studies Female Humans Aged Machine Learning Adult Prognosis Radiomics
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Evaluation and comparison of synthetic computed tomography algorithms with 3T MRI for prostate radiotherapy: AI-based versus bulk density method.

Journal of applied clinical medical physics Nov 29, 2024
PURPOSE: Synthetic computed tomography (sCT)-algorithms, which generate computed tomography images from magnetic resonance imaging data, are becoming part of the clinical radiotherapy workflow. The aim of this retrospective study was to evaluate and ...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Prostatic Neoplasms Retrospective Studies Organs at Risk Tomography, X-Ray Computed Male Humans Artificial Intelligence
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Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.

Journal of cardiovascular electrophysiology Nov 29, 2024
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...
Treatment Outcome Action Potentials Predictive Value of Tests Registries Fibrosis Male Middle Aged Risk Assessment Time Factors Recurrence Atrial Function, Left Pulmonary Veins Atrial Remodeling Atrial Fibrillation Heart Atria Heart Rate Catheter Ablation Humans Machine Learning Retrospective Studies Female Risk Factors Aged
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