AIMC Topic: Aged, 80 and over
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Classification for invasion depth of esophageal squamous cell carcinoma using a deep neural network compared with experienced endoscopists.
Gastrointestinal endoscopy
May 8, 2019
BACKGROUND AND AIMS: Cancer invasion depth is a critical factor affecting the choice of treatment in patients with superficial squamous cell carcinoma (SCC). However, the diagnosis of invasion depth is currently subjective and liable to interobserver...
Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.
Sensors (Basel, Switzerland)
May 8, 2019
Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify variations in response to physiological characteristics. In this paper, to analyze BP's normality based on oscillometric measurements, we use statistical...
Effects of combining modern recovery techniques with neurotrophic medication and standard treatment in stroke patients.
The Science of the total environment
May 7, 2019
Stroke is the main cause of disability after age 65, leaving survivors with sequels that require care and recovery treatment lasting years. It is estimated that by the year 2030 this pathology will be leading cause of mortality. To determine the effi...
A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction.
Radiology
May 7, 2019
Background Mammographic density improves the accuracy of breast cancer risk models. However, the use of breast density is limited by subjective assessment, variation across radiologists, and restricted data. A mammography-based deep learning (DL) mod...
Declining use of radical prostatectomy and pelvic lymphadenectomy despite more robotics: National population data over 15 years.
Asia-Pacific journal of clinical oncology
May 6, 2019
AIM: To describe national surgical patterns of prostate cancer (PCa) care considering radical prostatectomy with or without pelvic lymphadenectomy and consideration of robotic-assisted techniques.
Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.
EBioMedicine
May 3, 2019
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...
Aged, 80 and over
Young Adult
Adult
Sensitivity and Specificity
Male
Prognosis
Retrospective Studies
Tomography, X-Ray Computed
Female
Aged
Models, Biological
Hematoma
Odds Ratio
Glasgow Coma Scale
Middle Aged
ROC Curve
Image Processing, Computer-Assisted
Support Vector Machine
Cerebral Hemorrhage
Humans
Biomarkers
Defining Image Memorability Using the Visual Memory Schema.
IEEE transactions on pattern analysis and machine intelligence
May 2, 2019
Memorability of an image is a characteristic determined by the human observers' ability to remember images they have seen. Yet recent work on image memorability defines it as an intrinsic property that can be obtained independent of the observer. The...
Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model.
The Journal of arthroplasty
May 2, 2019
BACKGROUND: The primary objective was to develop and test an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition for total hip arthroplasty. The secondary objective was to create...
Robot-Assisted Reaching Performance of Chronic Stroke and Healthy Individuals in a Virtual Versus a Physical Environment: A Pilot Study.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 1, 2019
The aim of the current study was to examine the role of environment, whether virtual or physical, on robot-assisted reaching movements in chronic stroke and healthy individuals, within a single session. Twenty-three subjects participated in the curre...
Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.
European radiology
Apr 30, 2019
OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, sub...
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