AIMC Topic: Retrospective Studies

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F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BMC medical imaging Apr 28, 2025
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
Nomograms Positron Emission Tomography Computed Tomography Male Neoplasm Grading Middle Aged Radiopharmaceuticals Humans Deep Learning Retrospective Studies Lung Neoplasms Fluorodeoxyglucose F18 Female Adenocarcinoma of Lung Aged
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Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

Journal of medical Internet research Apr 28, 2025
BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians. Early identification and prediction of persistent SA-AKI are crucial.
Sepsis Prospective Studies Biomarkers Retrospective Studies Acute Kidney Injury Aged Male Middle Aged Intensive Care Units Female Humans Machine Learning
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Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Translational psychiatry Apr 27, 2025
Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervise...
Middle Aged Humans Female Depressive Disorder, Treatment-Resistant Treatment Outcome Aged Retrospective Studies Supervised Machine Learning Adult Electronic Health Records Transcranial Magnetic Stimulation Male
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Machine Learning to Predict Early Death Despite Pancreaticoduodenectomy.

The Journal of surgical research Apr 26, 2025
INTRODUCTION: About 25% of patients undergoing pancreaticoduodenectomy (PD) for right-sided pancreatic ductal adenocarcinoma (PDAC) die within 1 y of diagnosis. These patients carry all the risks of significant morbidity with no survival advantage wh...
Humans Machine Learning Retrospective Studies Medical Futility Risk Assessment Female Pancreatic Neoplasms Aged Carcinoma, Pancreatic Ductal Male Pancreaticoduodenectomy Middle Aged
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A Novel Natural Language Processing Model for Triaging Head and Neck Patient Appointments.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Apr 25, 2025
OBJECTIVE: Inaccurate patient triage contributes to suboptimal clinical capacity management and delays in patient care, which in cancer patients may significantly increase morbidity and mortality. We developed a natural language processing (NLP) mode...
Humans Retrospective Studies Female Head and Neck Neoplasms Aged Triage Adult Male Natural Language Processing Middle Aged Appointments and Schedules Referral and Consultation
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A novel cancer-associated fibroblast-related gene signature for predicting diffuse large B cell lymphoma prognosis using weighted gene co-expression network analysis and machine learning.

The Journal of international medical research Apr 25, 2025
ObjectiveOur objective was to investigate a novel cancer-associated fibroblast-related gene signature for predicting clinical outcomes in patients with diffuse large B cell lymphoma.MethodsThe cancer-associated fibroblast-related module genes were id...
Kaplan-Meier Estimate Humans Machine Learning Female Biomarkers, Tumor ROC Curve Lymphoma, Large B-Cell, Diffuse Prognosis Gene Regulatory Networks Male Retrospective Studies Gene Expression Regulation, Neoplastic Middle Aged Nomograms Gene Expression Profiling Cancer-Associated Fibroblasts Transcriptome
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Artificial Delayed-phase Technetium-99m MIBI Scintigraphy From Early-phase Scintigraphy Improves Identification of Hyperfunctioning Parathyroid Lesions in Patients With Hyperparathyroidism.

Clinical nuclear medicine Apr 24, 2025
PURPOSE: The aim of this study was to generate and validate artificial delayed-phase technetium-99m methoxyisobutylisonitrile scintigraphy (aMIBI) images from early-phase technetium-99m methoxyisobutylisonitrile scintigraphy (eMIBI) images.
Technetium Tc 99m Sestamibi Organotechnetium Compounds ROC Curve Hyperparathyroidism Parathyroid Glands Radionuclide Imaging Humans Retrospective Studies Female Male Middle Aged Time Factors Aged Adult
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Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.

Radiography (London, England : 1995) Apr 24, 2025
INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient ...
Aged Adult Male Middle Aged Humans Retrospective Studies Female Phantoms, Imaging Radiation Exposure Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Radiography, Thoracic
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Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart Apr 24, 2025
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...
Computed Tomography Angiography Coronary Stenosis Coronary Artery Disease Netherlands Retrospective Studies Sex Factors Electronic Health Records Coronary Vessels Humans Female Male Reproducibility of Results Machine Learning Middle Aged Aged Algorithms Predictive Value of Tests Coronary Angiography
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Prediction of significant congenital heart disease in infants and children using continuous wavelet transform and deep convolutional neural network with 12-lead electrocardiogram.

BMC pediatrics Apr 24, 2025
BACKGROUND: Congenital heart disease (CHD) affects approximately 1% of newborns and is a leading cause of mortality in early childhood. Despite the importance of early detection, current screening methods, such as pulse oximetry and auscultation, hav...
Humans Wavelet Analysis Neural Networks, Computer Deep Learning Heart Defects, Congenital Retrospective Studies Convolutional Neural Networks Child, Preschool Sensitivity and Specificity Electrocardiography Male Infant Female Infant, Newborn
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