AIMC Topic: Reproducibility of Results

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A superpixel-driven deep learning approach for the analysis of dermatological wounds.

Computer methods and programs in biomedicine Sep 13, 2019
BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi...
Support Vector Machine Principal Component Analysis Area Under Curve Bayes Theorem Dermatology Pattern Recognition, Automated Skin Ulcer Sensitivity and Specificity Humans Diagnosis, Computer-Assisted Machine Learning Deep Learning Algorithms Image Processing, Computer-Assisted Reproducibility of Results
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Machine Learning to Predict the Risk of Incident Heart Failure Hospitalization Among Patients With Diabetes: The WATCH-DM Risk Score.

Diabetes care Sep 13, 2019
OBJECTIVE: To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM).
Hospitalization Aged Male Middle Aged Risk Assessment Incidence Cohort Studies Time Factors Machine Learning Humans Clinical Trials as Topic Diabetes Mellitus, Type 2 Female Reproducibility of Results Outpatients Follow-Up Studies Risk Factors Predictive Value of Tests Heart Failure
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Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 11, 2019
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram (EEG) signals of patients with epilepsy, their conditions can be monito...
Machine Learning Fourier Analysis Algorithms Reproducibility of Results Humans Fuzzy Logic Support Vector Machine Neural Networks, Computer Principal Component Analysis Electroencephalography Epilepsy Seizures
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2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

Physics in medicine and biology Sep 11, 2019
We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. T...
Humans Machine Learning Reproducibility of Results Healthy Volunteers Respiration Dose Fractionation, Radiation Movement Radiotherapy, Image-Guided Ultrasonography Image Processing, Computer-Assisted Abdomen Radiotherapy Planning, Computer-Assisted
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PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Psychophysiology Sep 10, 2019
Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although ...
Cerebral Cortex Connectome Dissociative Disorders Depersonalization Male Middle Aged Stress Disorders, Post-Traumatic Magnetic Resonance Imaging Humans Machine Learning Female Reproducibility of Results Adult
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LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.

International journal of molecular sciences Sep 10, 2019
Long non-coding RNAs (lncRNAs) play a crucial role in the pathogenesis and development of complex diseases. Predicting potential lncRNA-disease associations can improve our understanding of the molecular mechanisms of human diseases and help identify...
Computational Biology MicroRNAs RNA, Long Noncoding Reproducibility of Results Sensitivity and Specificity Neoplasms Genetic Predisposition to Disease Humans Neural Networks, Computer Algorithms
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On the validity of memristor modeling in the neural network literature.

Neural networks : the official journal of the International Neural Network Society Sep 9, 2019
An analysis of the literature shows that there are two types of non-memristive models that have been widely used in the modeling of so-called "memristive" neural networks. Here, we demonstrate that such models have nothing in common with the concept ...
Reproducibility of Results Memory Neural Networks, Computer
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Utilizing supervised machine learning to identify microglia and astrocytes in situ: implications for large-scale image analysis and quantification.

Journal of neuroscience methods Sep 5, 2019
BACKGROUND: The evaluation of histological tissue samples plays a crucial role in deciphering preclinical disease and injury mechanisms. High-resolution images can be obtained quickly however data acquisition are often bottlenecked by manual analysis...
Mice Rats Microglia Astrocytes Reproducibility of Results Sensitivity and Specificity Animals Image Processing, Computer-Assisted Neurosciences Supervised Machine Learning Animals, Genetically Modified Fluorescent Antibody Technique Histological Techniques
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Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Circulation. Cardiovascular quality and outcomes Sep 5, 2019
BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, machine learning algorithms, and availability of large-scal...
Heart Rate Machine Learning Markov Chains Databases, Factual Action Potentials Pattern Recognition, Automated Prognosis Cardiovascular Diseases Humans Predictive Value of Tests Reproducibility of Results Diagnosis, Computer-Assisted Neural Networks, Computer Time Factors Signal Processing, Computer-Assisted Electrocardiography Workflow
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A deep learning method for image-based subject-specific local SAR assessment.

Magnetic resonance in medicine Sep 4, 2019
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to inclu...
Phantoms, Imaging Databases, Factual Prostatic Neoplasms Computer Simulation Deep Learning Humans Reproducibility of Results Prostate Image Processing, Computer-Assisted Neural Networks, Computer Male Healthy Volunteers Magnetic Resonance Imaging Algorithms Signal-To-Noise Ratio Models, Statistical
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