AIMC Topic: Proof of Concept Study
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A Single Session of Robot-Controlled Proprioceptive Training Modulates Functional Connectivity of Sensory Motor Networks and Improves Reaching Accuracy in Chronic Stroke.
Neurorehabilitation and neural repair
Dec 29, 2018
BACKGROUND: Passive robot-generated arm movements in conjunction with proprioceptive decision making and feedback modulate functional connectivity (FC) in sensory motor networks and improve sensorimotor adaptation in normal individuals. This proof-of...
Prediction of Lymph Node Maximum Standardized Uptake Value in Patients With Cancer Using a 3D Convolutional Neural Network: A Proof-of-Concept Study.
AJR. American journal of roentgenology
Dec 12, 2018
OBJECTIVE: The purpose of this study is to determine whether a convolutional neural network (CNN) can predict the maximum standardized uptake value (SUV) of lymph nodes in patients with cancer using the unenhanced CT images from a PET/CT examination,...
Lymphatic Metastasis
Predictive Value of Tests
Positron Emission Tomography Computed Tomography
Radiopharmaceuticals
Humans
Fluorodeoxyglucose F18
Adult
Tomography, X-Ray Computed
Neural Networks, Computer
Proof of Concept Study
Middle Aged
Aged
Retrospective Studies
Neoplasms
Aged, 80 and over
Imaging, Three-Dimensional
Young Adult
Deep learning for detecting tumour-infiltrating lymphocytes in testicular germ cell tumours.
Journal of clinical pathology
Dec 5, 2018
AIMS: To evaluate if a deep learning algorithm can be trained to identify tumour-infiltrating lymphocytes (TILs) in tissue samples of testicular germ cell tumours and to assess whether the TIL counts correlate with relapse status of the patient.
Selecting Test Cases from the Electronic Health Record for Software Testing of Knowledge-Based Clinical Decision Support Systems.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Software testing of knowledge-based clinical decision support systems is challenging, labor intensive, and expensive; yet, testing is necessary since clinical applications have heightened consequences. Thoughtful test case selection improves testing ...
Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for...
A Biologically Inspired Approach for Robot Depth Estimation.
Computational intelligence and neuroscience
Aug 23, 2018
Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated. In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks. So, from neuroscience findings, a h...
Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.
JACC. Cardiovascular imaging
Aug 15, 2018
Development and Validation of Machine Learning Models for Prediction of 1-Year Mortality Utilizing Electronic Medical Record Data Available at the End of Hospitalization in Multicondition Patients: a Proof-of-Concept Study.
Journal of general internal medicine
Jan 30, 2018
BACKGROUND: Predicting death in a cohort of clinically diverse, multicondition hospitalized patients is difficult. Prognostic models that use electronic medical record (EMR) data to determine 1-year death risk can improve end-of-life planning and ris...
Pseudoneglect in Visual Search: Behavioral Evidence and Connectional Constraints in Simulated Neural Circuitry.
eNeuro
Dec 28, 2017
Most people tend to bisect horizontal lines slightly to the left of their true center (pseudoneglect) and start visual search from left-sided items. This physiological leftward spatial bias may depend on hemispheric asymmetries in the organization of...
Computer Simulation and Optimization of Cranial Vault Distraction.
The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
Dec 14, 2017
OBJECTIVE: The objective of this study was to validate the proof of concept of a computer-simulated cranial distraction, demonstrating accurate shape and end volume.
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