AIMC Topic: Reproducibility of Results

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Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

Journal of X-ray science and technology Jan 1, 2020
OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease.
Lung Humans Algorithms Deep Learning Early Diagnosis Tomography, X-Ray Computed Pneumonia Neural Networks, Computer Reproducibility of Results Betacoronavirus Coronavirus Infections Pandemics Pneumonia, Viral SARS-CoV-2 COVID-19
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Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

Journal of X-ray science and technology Jan 1, 2020
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. ...
Databases, Factual Radiography, Thoracic Tomography, X-Ray Computed Neural Networks, Computer Deep Learning Betacoronavirus Pneumonia, Viral Reproducibility of Results Pandemics Diagnosis, Differential SARS-CoV-2 COVID-19 Pneumonia Humans Algorithms Coronavirus Infections
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Electroencephalogram-Based Emotion Recognition Using a Particle Swarm Optimization-Derived Support Vector Machine Classifier.

Critical reviews in biomedical engineering Jan 1, 2020
We sort human emotions using Russell's circumplex model of emotion by classifying electroencephalogram (EEG) signals from 25 subjects into four discrete states, namely, happy, sad, angry, and relaxed. After acquiring signals, we use a standard databa...
Emotions Electroencephalography Signal Processing, Computer-Assisted Electrodes Recognition, Psychology Pattern Recognition, Automated Humans Male Wavelet Analysis Algorithms Deep Learning Female Adolescent Support Vector Machine Reproducibility of Results Young Adult Adult
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Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated.
Humans Machine Learning Aged Aged, 80 and over Male Retrospective Studies Data Analysis Dementia Electronic Health Records Forecasting Female Mental Disorders Reproducibility of Results Databases, Factual
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[Diagnosis of malignant pleural effusions using convolutional neural networks by the morphometric image analysis of facies of pleural exudate].

Khirurgiia Jan 1, 2020
OBJECTIVE: To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.
Exudates and Transudates Pleural Effusion, Malignant Reproducibility of Results Sensitivity and Specificity Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Computational Intelligence Techniques for Assessing Anthropometric Indices Changes in Female Athletes.

Current medical imaging Jan 1, 2020
BACKGROUND: Physical characteristics including body size and configuration, are considered as one of the key influences on the optimum performance in athletes. Despite several analyzing methods for modeling the slimming estimation in terms of reducti...
Middle Aged Plant Extracts Fuzzy Logic Waist Circumference Female Body Size Reproducibility of Results Carum Young Adult Adult Athletes Humans Anthropometry Artificial Intelligence
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Intelligent infusion controller with a physiological information feedback function.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2020
BACKGROUND: In hospitals, some problems still exist, such as transfusion reaction that cannot be dealt with in time, medical staff cannot observe the physiological information of the infusion patients in real time, and the infusion speed cannot be co...
Fuzzy Logic Infusions, Intravenous Heart Rate Transfusion Reaction Algorithms Reproducibility of Results Feedback Wearable Electronic Devices Humans
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Automated sample preparation with SP3 for low-input clinical proteomics.

Molecular systems biology Jan 1, 2020
High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot ...
Proteomics Adenocarcinoma Mass Spectrometry Chromatography, Liquid Proteins Humans Software Reproducibility of Results Lung Neoplasms Robotics Workflow HeLa Cells Specimen Handling
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Machine Learning Predictive Models Can Improve Efficacy of Clinical Trials for Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and also would be responsive to the therapeutic intervention being studied (i.e., drug arm). ...
Neuroimaging Clinical Trials as Topic Clinical Trials, Phase III as Topic Mental Status and Dementia Tests Magnetic Resonance Imaging Predictive Value of Tests Sample Size Alzheimer Disease Databases, Factual Humans Female Machine Learning Reproducibility of Results Male Algorithms Aged Aged, 80 and over Cognitive Dysfunction Research Design Sensitivity and Specificity Follow-Up Studies
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Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors.

Diagnostic and interventional radiology (Ankara, Turkey) Jan 1, 2020
PURPOSE: To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) automatic segmentation algorithms with those of well-established semi-automatic (interactive) methods for determining liver volume in living liver trans...
Image Processing, Computer-Assisted Liver Organ Size Humans Living Donors Tomography, X-Ray Computed Liver Transplantation Reproducibility of Results Deep Learning
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