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Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Medical image analysis
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient a...

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 1: From Methodology to Clinical Implementation.

Journal of the American College of Radiology : JACR
Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. Mo...

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Journal of the American College of Radiology : JACR
Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. Mo...

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework.

Artificial intelligence in medicine
Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data....
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Kinematic measures for upper limb robot-assisted therapy following stroke and correlations with clinical outcome measures: A review.

Medical engineering & physics
AIM OF THE STUDY: This review classifies the kinematic measures used to evaluate post-stroke motor impairment following upper limb robot-assisted rehabilitation and investigates their correlations with clinical outcome measures.

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression.

Scientific reports
Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screening is complicated by the fact that the accuracy of noninvasive testing lacks specificity and sensitivity to make and stage the diagnosis. Currently n...

Comparison of proximal versus distal upper-limb robotic rehabilitation on motor performance after stroke: a cluster controlled trial.

Scientific reports
This study examined the treatment efficacy of proximal-emphasized robotic rehabilitation by using the InMotion ARM (P-IMT) versus distal-emphasized robotic rehabilitation by using the InMotion WRIST (D-IMT) in patients with stroke. A total of 40 pati...

Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques.

Biomedical engineering online
PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing ...

A review of influenza detection and prediction through social networking sites.

Theoretical biology & medical modelling
Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases ...