AIMC Topic: 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...
Humans Machine Learning Retrospective Studies Mouth Neoplasms Radiotherapy, Adjuvant Adult Male Middle Aged Sarcopenia Muscle, Skeletal Tomography, X-Ray Computed Female Carcinoma, Squamous Cell Aged
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CT-based clinical-radiomics model to predict progression and drive clinical applicability in locally advanced head and neck cancer.

European radiology Dec 20, 2024
BACKGROUND: Definitive chemoradiation is the primary treatment for locally advanced head and neck carcinoma (LAHNSCC). Optimising outcome predictions requires validated biomarkers, since TNM8 and HPV could have limitations. Radiomics may enhance risk...
Middle Aged Disease Progression Head and Neck Neoplasms Chemoradiotherapy Aged Humans Adult Tomography, X-Ray Computed Sensitivity and Specificity Female Radiomics Male
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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 Humans Signal-To-Noise Ratio Middle Aged Computed Tomography Angiography Deep Learning Myocardial Perfusion Imaging Iodine Radiographic Image Enhancement Contrast Media 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.
Carcinoma, Hepatocellular Predictive Value of Tests Hepatectomy Anastomotic Leak Cholangiocarcinoma Male Middle Aged Risk Assessment Liver Neoplasms Databases, Factual Retrospective Studies Female Humans Risk Factors Aged Machine Learning Decision Support Techniques
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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...
Uveitis Male Middle Aged Adolescent ROC Curve Humans Neural Networks, Computer Machine Learning Algorithms Retrospective Studies Female Aged Young Adult Adult Sensitivity and Specificity
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Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

Journal of applied clinical medical physics Dec 20, 2024
PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential...
Adult Breast Neoplasms Radiomics Echocardiography Middle Aged Humans Machine Learning Female Aged Cardiotoxicity Unilateral Breast Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiation Injuries
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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...
Spinal Neoplasms Tomography, X-Ray Computed Female Aged Male Middle Aged Deep Learning Treatment Outcome Obesity Sarcopenia Body Composition Humans Phenotype Prognosis Retrospective Studies
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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.
Humans Retrospective Studies Female Aged Adult Male Middle Aged Severity of Illness Index ROC Curve Liver Cirrhosis Biopsy Support Vector Machine Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Reference Standards Liver Elasticity Imaging Techniques Principal Component Analysis Echo-Planar Imaging Area Under Curve
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Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.

BMJ open Dec 20, 2024
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
Male Randomized Controlled Trials as Topic Humans Middle Aged Female Machine Learning Risk Assessment Elective Surgical Procedures Aged Prospective Studies Singapore Postoperative Complications Aged, 80 and over Intensive Care Units Hospitals, General Decision Support Systems, Clinical Young Adult Perioperative Care Adult
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Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.

Sensors (Basel, Switzerland) Dec 20, 2024
Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early ...
Aged Magnetic Resonance Imaging Male Parkinson Disease Humans Middle Aged Machine Learning Logistic Models Brain Support Vector Machine Female
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