AIMC Topic: Retrospective Studies

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Using clinical data to reclassify ESUS patients to large artery atherosclerotic or cardioembolic stroke mechanisms.

Journal of neurology Dec 21, 2024
PURPOSE: Embolic stroke of unidentified source (ESUS) represents 10-25% of all ischemic strokes. Our goal was to determine whether ESUS could be reclassified to cardioembolic (CE) or large-artery atherosclerosis (LAA) with machine learning (ML) using...
Female Aged Aged, 80 and over Humans Male Middle Aged Machine Learning Retrospective Studies Ischemic Stroke Atherosclerosis Embolic Stroke
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Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1-L5 lumbar spine.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer Dec 21, 2024
PURPOSE: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colon cancer treatment. Body composition analysis may enable tailored interventions thereby supporting the mitigation of chemotherapy toxic effects. This ...
Imaging, Three-Dimensional Dose-Response Relationship, Drug Body Composition Lumbar Vertebrae Aged, 80 and over Colonic Neoplasms Humans Adult Chemotherapy, Adjuvant Artificial Intelligence Male Middle Aged Antineoplastic Agents Retrospective Studies Tomography, X-Ray Computed Female Aged
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Identifying threshold of CT-defined muscle loss after radiotherapy for survival in oral cavity cancer using machine learning.

European radiology Dec 20, 2024
OBJECTIVES: Muscle loss after radiotherapy is associated with poorer survival in patients with oral cavity squamous cell carcinoma (OCSCC). However, the threshold of muscle loss remains unclear. This study aimed to utilize explainable artificial inte...
Muscle, Skeletal Machine Learning Mouth Neoplasms Retrospective Studies Radiotherapy, Adjuvant Tomography, X-Ray Computed Humans Aged Female Carcinoma, Squamous Cell Adult Male Middle Aged Sarcopenia
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Deep learning model for low-dose CT late iodine enhancement imaging and extracellular volume quantification.

European radiology Dec 20, 2024
OBJECTIVES: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (LIE) images and enable accurate extracellular volume (ECV) quantification.
Retrospective Studies Tomography, X-Ray Computed Female Aged Male Radiation Dosage Middle Aged Signal-To-Noise Ratio Deep Learning Humans Computed Tomography Angiography Iodine Myocardial Perfusion Imaging Contrast Media Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted
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Machine learning based prediction model for bile leak following hepatectomy for liver cancer.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 20, 2024
OBJECTIVE: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.
Cholangiocarcinoma Humans Machine Learning Carcinoma, Hepatocellular Aged Predictive Value of Tests Decision Support Techniques Male Hepatectomy Middle Aged Databases, Factual Anastomotic Leak Risk Assessment Retrospective Studies Liver Neoplasms Female Risk Factors
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Neural networks for predicting etiological diagnosis of uveitis.

Eye (London, England) Dec 20, 2024
BACKGROUND/OBJECTIVES: The large number and heterogeneity of causes of uveitis make the etiological diagnosis a complex task. The clinician must consider all the information concerning the ophthalmological and extra-ophthalmological features of the p...
Young Adult Adult Sensitivity and Specificity Male Middle Aged Algorithms Retrospective Studies Female Aged Adolescent ROC Curve Uveitis Humans Neural Networks, Computer Machine Learning
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Assessing the prognostic impact of body composition phenotypes on surgical outcomes and survival in patients with spinal metastasis: a deep learning approach to preoperative CT analysis.

Journal of neurosurgery. Spine Dec 20, 2024
OBJECTIVE: The prognostic significance of body composition phenotypes for survival in patients undergoing surgical intervention for spinal metastases has not yet been elucidated. This study aimed to elucidate the impact of body composition phenotypes...
Prognosis Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Phenotype Obesity Sarcopenia Body Composition Spinal Neoplasms Male Middle Aged Deep Learning Treatment Outcome
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Diagnostic accuracy of texture analysis applied to T- and T-Relaxation maps for liver fibrosis classification via machine-learning algorithms with liver histology as reference standard.

European journal of radiology Dec 20, 2024
OBJECTIVES: To explore texture analysis' ability on T and T relaxation maps to classify liver fibrosis into no-to-mild liver fibrosis (nmF) versus severe fibrosis (sF) group using machine learning algorithms and histology as reference standard.
Adult Male Middle Aged Severity of Illness Index ROC Curve Liver Cirrhosis Support Vector Machine Magnetic Resonance Imaging Liver Principal Component Analysis Humans Retrospective Studies Female Aged Area Under Curve Biopsy Elasticity Imaging Techniques Image Interpretation, Computer-Assisted Echo-Planar Imaging Reference Standards
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Ocular biometric parameters in Chinese preschool children and physiological axial length growth prediction using machine learning algorithms: a retrospective cross-sectional study.

BMJ open Dec 20, 2024
OBJECTIVES: To examine the ocular biometric parameters and predict the annual growth rate of the physiological axial length (AL) in Chinese preschool children aged 4-6 years old.
China Child, Preschool Child Female East Asian People Humans Cross-Sectional Studies Biometry Machine Learning Male Axial Length, Eye Algorithms Refraction, Ocular Hyperopia Retrospective Studies Myopia
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AI-assisted detection for chest X-rays (AID-CXR): a multi-reader multi-case study protocol.

BMJ open Dec 20, 2024
INTRODUCTION: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormal...
Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Lung Diseases Artificial Intelligence Research Design Radiography, Thoracic Retrospective Studies ROC Curve
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