AIMC Topic: Retrospective Studies

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Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.

Asian journal of andrology Oct 4, 2024
Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) ...
Adult Male Deep Learning Ultrasonography Sperm Retrieval Humans Retrospective Studies Testis Azoospermia Sertoli Cell-Only Syndrome
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Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography.

Diagnostic and interventional imaging Oct 4, 2024
PURPOSE: The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA).
Computed Tomography Angiography Photons Retrospective Studies Female Aged Sensitivity and Specificity Male Middle Aged Deep Learning Coronary Angiography Coronary Artery Disease Humans
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Clinical Impact of Radiologist's Alert System on Patient Care for High-risk Incidental CT Findings: A Machine Learning-Based Risk Factor Analysis.

Academic radiology Oct 4, 2024
RATIONALE AND OBJECTIVES: Efficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist's Alert and Pat...
Adult Male Middle Aged Risk Assessment Radiologists Tomography, X-Ray Computed Incidental Findings Female Risk Factors Humans Aged Machine Learning Aged, 80 and over Retrospective Studies
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Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract Oct 3, 2024
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...
Carcinoma, Signet Ring Cell Machine Learning Gastrectomy Linear Models Prognosis Middle Aged Retrospective Studies Humans Lymphatic Metastasis Female Lymph Node Excision Aged Neoplasm Staging Aged, 80 and over Neoplasm Recurrence, Local Adult Stomach Neoplasms Survival Rate Male
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Machine learning model to predict early recurrence in patients with perihilar cholangiocarcinoma planned treatment with curative resection: a multicenter study.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract Oct 3, 2024
BACKGROUND: Early recurrence is the leading cause of death for patients with perihilar cholangiocarcinoma (pCCA) after surgery. Identifying high-risk patients preoperatively is important. This study aimed to construct a preoperative prediction model ...
Middle Aged Risk Assessment ROC Curve Neoplasm Invasiveness Predictive Value of Tests Neoplasm Recurrence, Local Bile Duct Neoplasms Portal Vein Kaplan-Meier Estimate Machine Learning Klatskin Tumor Humans Retrospective Studies Female Aged Male
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Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.

Annals of Saudi medicine Oct 3, 2024
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...
Noncommunicable Diseases Middle Aged Prevalence Logistic Models Dyslipidemias Saudi Arabia Humans Hypertension Multimorbidity Adolescent Female Mental Disorders Diabetes Mellitus Obesity Aged Retrospective Studies Natural Language Processing Young Adult Electronic Health Records Adult Male
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Comparison of Patients With and Without Predicted Surgical Indication Between Clusters of Adult Spine Deformity (ASD) Patients.

Spine Oct 1, 2024
STUDY DESIGN: Multicentric, retrospective analysis of prospectively collected data.
Humans Machine Learning Retrospective Studies Treatment Outcome Female Follow-Up Studies Cluster Analysis Aged Scoliosis Adult Minimal Clinically Important Difference Male Middle Aged
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Machine learning models for discriminating clinically significant from clinically insignificant prostate cancer using bi-parametric magnetic resonance imaging.

Diagnostic and interventional radiology (Ankara, Turkey) Oct 1, 2024
PURPOSE: This study aims to demonstrate the performance of machine learning algorithms to distinguish clinically significant prostate cancer (csPCa) from clinically insignificant prostate cancer (ciPCa) in prostate bi-parametric magnetic resonance im...
Prostate Image Interpretation, Computer-Assisted Support Vector Machine Magnetic Resonance Imaging Prostatic Neoplasms Humans Neoplasm Grading Machine Learning Algorithms Retrospective Studies Aged Male Middle Aged
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Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.

Journal of magnetic resonance imaging : JMRI Oct 1, 2024
BACKGROUND: Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI.
Retrospective Studies Female Reproducibility of Results Aged Adult Humans Algorithms Myocardial Ischemia Magnetic Resonance Imaging, Cine Cardiomyopathy, Dilated Image Processing, Computer-Assisted Heart Heart Ventricles Image Interpretation, Computer-Assisted Sensitivity and Specificity Cardiomyopathy, Hypertrophic Male Middle Aged Deep Learning
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Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia.

Circulation journal : official journal of the Japanese Circulation Society Oct 1, 2024
BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce mortality associated with ventricular arrhythmia in high-risk patients with cardiovascular disease. Machine learning (ML) approaches are promising tools in arrhythmia research; however...
Cluster Analysis Arrhythmias, Cardiac Tachycardia, Ventricular Humans Defibrillators, Implantable Aged Machine Learning Retrospective Studies Male Female Middle Aged Electrocardiography
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