AIMC Topic: Aged, 80 and over

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Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports Nov 2, 2020
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...
Humans Machine Learning Algorithms Biomarkers Brain ROC Curve Prognosis Cognition Female Magnetic Resonance Imaging Predictive Value of Tests Aged Amyloid beta-Peptides Aged, 80 and over Cerebral Amyloid Angiopathy Male
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Automated Lung Segmentation on Chest Computed Tomography Images with Extensive Lung Parenchymal Abnormalities Using a Deep Neural Network.

Korean journal of radiology Oct 30, 2020
OBJECTIVE: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images.
Male Automation Tomography, X-Ray Computed Humans Female Databases, Factual Middle Aged Aged Lung Aged, 80 and over Deep Learning Adult Lung Diseases, Interstitial
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Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study.

Scientific reports Oct 30, 2020
The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients effectively. This study used the nationwide cohort of South Korea to develop a machine learning model ...
Middle Aged Models, Statistical Coronavirus Infections Mortality Pneumonia, Viral Republic of Korea Female Aged Humans Aged, 80 and over Machine Learning Adult Pandemics Male COVID-19
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Deep phenotype unsupervised machine learning revealed the significance of pachychoroid features in etiology and visual prognosis of age-related macular degeneration.

Scientific reports Oct 28, 2020
Unsupervised machine learning has received increased attention in clinical research because it allows researchers to identify novel and objective viewpoints for diseases with complex clinical characteristics. In this study, we applied a deep phenotyp...
Aged, 80 and over Humans Male Prognosis Angiogenesis Inhibitors Retrospective Studies Macular Degeneration Unsupervised Machine Learning Female Intravitreal Injections Choroid Aged Recombinant Fusion Proteins Receptors, Vascular Endothelial Growth Factor Choroidal Neovascularization
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Can artificial intelligence distinguish between malignant and benign mediastinal lymph nodes using sonographic features on EBUS images?

Current medical research and opinion Oct 24, 2020
AIMS: This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approach adequately described mediastinal lymphadenop...
Humans Artificial Intelligence Female Aged Mediastinum Diagnosis, Computer-Assisted Ultrasonography Aged, 80 and over Image Processing, Computer-Assisted Young Adult Lymph Nodes Adult Predictive Value of Tests Male Middle Aged
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The prognostic role of end-of-treatment FDG-PET/CT in diffuse large B cell lymphoma: a pilot study application of neural networks to predict time-to-event.

Annals of nuclear medicine Oct 22, 2020
PURPOSE: To evaluate the prognostic role of end-of-treatment (EoT) FDG-PET/CT parameters in diffuse large B cell lymphoma (DLBCL), and then to explore a pilot application of Neural Networks (NN) in predicting time-to-relapse.
Lymphoma, Large B-Cell, Diffuse Male Middle Aged Pilot Projects Time Factors Positron Emission Tomography Computed Tomography Fluorodeoxyglucose F18 Recurrence Female Aged Aged, 80 and over Young Adult Adult Humans Neural Networks, Computer Prognosis Retrospective Studies
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Volumetric breast density estimation on MRI using explainable deep learning regression.

Scientific reports Oct 22, 2020
To purpose of this paper was to assess the feasibility of volumetric breast density estimations on MRI without segmentations accompanied with an explainability step. A total of 615 patients with breast cancer were included for volumetric breast densi...
Aged, 80 and over Adult Breast Neoplasms Middle Aged Deep Learning Algorithms Prospective Studies Prognosis Female Aged Breast Density Carcinoma, Lobular Image Processing, Computer-Assisted Follow-Up Studies Magnetic Resonance Imaging Neoplasm Invasiveness Carcinoma, Ductal, Breast Humans Neural Networks, Computer
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The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.

The Journal of surgical research Oct 21, 2020
BACKGROUND: Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal he...
Risk Assessment Postoperative Complications Adolescent Hernia, Inguinal Hospital Mortality Aged, 80 and over Patient Readmission Treatment Outcome Logistic Models Young Adult Elective Surgical Procedures Quality Improvement Humans Adult Feasibility Studies Herniorrhaphy Neural Networks, Computer Male Female Middle Aged Risk Factors Aged
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Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.

Clinical physiology and functional imaging Oct 18, 2020
INTRODUCTION: Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods ca...
Humans Positron Emission Tomography Computed Tomography Artificial Intelligence Prostatic Neoplasms Aged Feasibility Studies Aged, 80 and over Survival Analysis Lymph Nodes Image Interpretation, Computer-Assisted Lymphatic Metastasis Adult Predictive Value of Tests Male Middle Aged
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Effects of walking distance over robot-assisted training on walking ability in chronic stroke patients.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Oct 16, 2020
An understanding of the dose-response during training is important to identify the rehabilitation programs to obtain the improvement in chronic stroke patients. The purpose of this study was to determine whether distance-dose (distance walked across ...
Exoskeleton Device Robotics Humans Stroke Rehabilitation Female Walk Test Stroke Adult Aged Walking Male Aged, 80 and over Gait Middle Aged Young Adult Exercise Therapy Treatment Outcome Chronic Disease
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