AIMC Topic: Aged, 80 and over
Clear Filters Showing 1981 to 1990 of 3475 articles
Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review.
Journal of the American Medical Directors Association
Nov 29, 2019
OBJECTIVE: The objective of the article is to analyze the effects of the end-effector technology for gait rehabilitation on acute, subacute, and chronic stroke in order to verify the efficacy of the treatment in older people, based on evidence from r...
Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept.
Clinical radiology
Nov 29, 2019
AIM: To investigate the feasibility of applying a deep convolutional neural network (CNN) for detection/localisation of acute proximal femoral fractures (APFFs) on hip radiographs.
Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics.
IEEE journal of biomedical and health informatics
Nov 28, 2019
OBJECTIVE: Histologic grade and Ki-67 proliferation status are important clinical indictors for breast cancer prognosis and treatment. The purpose of this study is to improve prediction accuracy of these clinical indicators based on tumor radiomic an...
Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists.
Scientific reports
Nov 28, 2019
Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learning-based US CAD system (dCAD) for the diagnosis of thyroid nodules and compare its performance with ...
Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.
Scientific reports
Nov 28, 2019
Radiogenomics investigates the relationship between imaging phenotypes and genetic expression. Breast cancer is a heterogeneous disease that manifests complex genetic changes and various prognosis and treatment response. We investigate the value of m...
Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.
Journal of cutaneous pathology
Nov 27, 2019
PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which ...
Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions.
Ultrasound in medicine & biology
Nov 27, 2019
The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for cla...
Brain age prediction using deep learning uncovers associated sequence variants.
Nature communications
Nov 27, 2019
Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual's predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here...
Automatic Quality Assessment of Transperineal Ultrasound Images of the Male Pelvic Region, Using Deep Learning.
Ultrasound in medicine & biology
Nov 25, 2019
Ultrasound guidance is not in widespread use in prostate cancer radiotherapy workflows. This can be partially attributed to the need for image interpretation by a trained operator during ultrasound image acquisition. In this work, a one-class regress...
Radiomics based on F-FDG PET/CT could differentiate breast carcinoma from breast lymphoma using machine-learning approach: A preliminary study.
Cancer medicine
Nov 25, 2019
PURPOSE: Our study assessed the ability F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) radiomics to differentiate breast carcinoma from breast lymphoma using machine-learning approach.
Humans
ROC Curve
Image Processing, Computer-Assisted
Follow-Up Studies
Lymphoma
Diagnosis, Differential
Positron Emission Tomography Computed Tomography
Radiopharmaceuticals
Fluorodeoxyglucose F18
Machine Learning
Prognosis
Retrospective Studies
Female
Aged
Aged, 80 and over
Adult
Breast Neoplasms
Middle Aged
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