AIMC Topic: Aged, 80 and over

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Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.

BMC cancer Nov 24, 2021
BACKGROUND: Radiomics may provide more objective and accurate predictions for extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models based on magnetic resonance imaging (MRI) and machine learning to preoperatively predict...
Cholangiocarcinoma Retrospective Studies Female Aged Aged, 80 and over Adult Magnetic Resonance Imaging Sensitivity and Specificity Predictive Value of Tests Area Under Curve Humans Neoplasm Grading Machine Learning Bile Duct Neoplasms Algorithms Male Middle Aged ROC Curve Adenocarcinoma Lymphatic Metastasis
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Analyzing artificial intelligence systems for the prediction of atrial fibrillation from sinus-rhythm ECGs including demographics and feature visualization.

Scientific reports Nov 23, 2021
Atrial fibrillation (AF) is an abnormal heart rhythm, asymptomatic in many cases, that causes several health problems and mortality in population. This retrospective study evaluates the ability of different AI-based models to predict future episodes ...
Humans Artificial Intelligence Prognosis Retrospective Studies Female Risk Factors Aged Aged, 80 and over Young Adult Adult Area Under Curve Male Middle Aged Registries Adolescent Atrial Fibrillation Electrocardiography Heart Rate Follow-Up Studies Demography
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Combination of artificial intelligence-based endoscopy and miR148a methylation for gastric indefinite dysplasia diagnosis.

Journal of clinical laboratory analysis Nov 22, 2021
BACKGROUND AND AIM: Gastrointestinal endoscopy and biopsy-based pathological findings are needed to diagnose early gastric cancer. However, the information of biopsy specimen is limited because of the topical procedure; therefore, pathology doctors s...
Early Detection of Cancer MicroRNAs Endoscopy, Gastrointestinal Stomach Endoscopic Mucosal Resection Humans Artificial Intelligence Female Aged Aged, 80 and over Stomach Neoplasms Biomarkers, Tumor Male Middle Aged Diagnosis, Computer-Assisted DNA Methylation
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Effect of data leakage in brain MRI classification using 2D convolutional neural networks.

Scientific reports Nov 19, 2021
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Image Interpretation, Computer-Assisted Neuroimaging Aged Aged, 80 and over Cross-Sectional Studies Male Middle Aged Case-Control Studies Deep Learning Magnetic Resonance Imaging Parkinson Disease Predictive Value of Tests Alzheimer Disease Humans Neural Networks, Computer Brain Female Reproducibility of Results
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Development and validation of a supervised deep learning algorithm for automated whole-slide programmed death-ligand 1 tumour proportion score assessment in non-small cell lung cancer.

Histopathology Nov 16, 2021
AIMS: Immunohistochemical programmed death-ligand 1 (PD-L1) staining to predict responsiveness to immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has several drawbacks: a robust gold standard is lacking, and there is substa...
Humans Algorithms Female Deep Learning Aged Lung Neoplasms Aged, 80 and over B7-H1 Antigen Male Carcinoma, Non-Small-Cell Lung Middle Aged
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Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.

Cell reports. Medicine Nov 16, 2021
Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and...
Treatment Outcome Male Humans Hepatic Artery Biopsy Middle Aged Female Supervised Machine Learning Transcriptome Aged Chemoembolization, Therapeutic Liver Neoplasms Aged, 80 and over Tumor Hypoxia Carcinoma, Hepatocellular Adult
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Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

Gynecologic oncology Nov 15, 2021
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...
Female Aged Aged, 80 and over Young Adult Adult Humans Machine Learning Databases, Factual Lymphatic Metastasis Predictive Value of Tests Neoplasm Staging Endometrial Neoplasms Middle Aged Cohort Studies Lymph Nodes United States Adenocarcinoma
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Deep-learning image-reconstruction algorithm for dual-energy CT angiography with reduced iodine dose: preliminary results.

Clinical radiology Nov 12, 2021
AIM: To evaluate the computed tomography (CT) attenuation values, background noise, arterial depiction, and image quality in whole-body dual-energy CT angiography (DECTA) at 40 keV with a reduced iodine dose using deep-learning image reconstruction (...
Aortic Diseases Whole Body Imaging Radiography, Dual-Energy Scanned Projection Female Aged Deep Learning Aged, 80 and over Humans Iodine Male Contrast Media Middle Aged Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Radiographic Image Enhancement
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A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Nutrients Nov 10, 2021
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...
Diagnostic Imaging Malnutrition Japan Deglutition Disorders Humans Mental Recall Machine Learning Aged, 80 and over Pneumonia, Aspiration Algorithms Cross-Sectional Studies Recognition, Psychology Female Male Aged Body Mass Index Sarcopenia
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A priori prediction of local failure in brain metastasis after hypo-fractionated stereotactic radiotherapy using quantitative MRI and machine learning.

Scientific reports Nov 3, 2021
This study investigated the effectiveness of pre-treatment quantitative MRI and clinical features along with machine learning techniques to predict local failure in patients with brain metastasis treated with hypo-fractionated stereotactic radiation ...
Precision Medicine Prognosis Retrospective Studies Female Aged Aged, 80 and over Humans Machine Learning Neoplasms ROC Curve Follow-Up Studies Magnetic Resonance Imaging Radiosurgery Radiation Dose Hypofractionation Young Adult Adult Brain Neoplasms Male Middle Aged
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