AIMC Topic: Reproducibility of Results

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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.

Genomics, proteomics & bioinformatics Sep 27, 2018
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Amino Acids Humans Internet Neural Networks, Computer Software Amino Acid Sequence Reproducibility of Results Nitrosation Deep Learning Proteins
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Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

American journal of physiology. Renal physiology Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Workflow Kidney Glomerulus Microscopy Image Interpretation, Computer-Assisted Mice, Transgenic Pattern Recognition, Automated Species Specificity Mice, Inbred C57BL Humans Kidney Diseases Machine Learning Predictive Value of Tests Male Software Biopsy Female Reproducibility of Results Diagnosis, Computer-Assisted Animals Rats Automation, Laboratory Disease Models, Animal Phenotype
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Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has attracted increasing attention, since a large number of subjects from multiple centers are beneficial for investigating the pathological changes of A...
Autism Spectrum Disorder Humans Reproducibility of Results Machine Learning Sensitivity and Specificity Algorithms Databases, Factual
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Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet () that learns to generate clinically relevant visual attention maps using sonographer gaze tracking data on input ultrasound (US) video frames so as to assist st...
Humans Neural Networks, Computer Algorithms Reproducibility of Results Image Processing, Computer-Assisted Attention Fetus Sensitivity and Specificity Eye Movements
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Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...
Machine Learning Pattern Recognition, Automated Humans Reproducibility of Results Algorithms Sensitivity and Specificity Pregnancy Ultrasonography Female Placenta
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Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning based Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
This paper introduces an unsupervised adversarial similarity network for image registration. Unlike existing deep learning registration frameworks, our approach does not require ground-truth deformations and specific similarity metrics. We connect a ...
Magnetic Resonance Imaging Reproducibility of Results Sensitivity and Specificity Deep Learning Image Processing, Computer-Assisted Humans Machine Learning Algorithms Brain
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Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

Journal of magnetic resonance imaging : JMRI Sep 25, 2018
BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.
Reproducibility of Results Aged Cross-Sectional Studies Middle Aged Algorithms Prospective Studies Osteoporosis Female Magnetic Resonance Imaging Linear Models Osteoporotic Fractures Case-Control Studies ROC Curve Image Processing, Computer-Assisted Body Mass Index Humans Machine Learning
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Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.

Radiology Sep 25, 2018
Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...
Humans Algorithms Middle Aged Deep Learning Adolescent Lung Neoplasms Radiography, Thoracic Aged, 80 and over Retrospective Studies Multiple Pulmonary Nodules Young Adult Female Radiographic Image Interpretation, Computer-Assisted Adult Reproducibility of Results Male Aged
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Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Journal of clinical monitoring and computing Sep 24, 2018
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...
Reproducibility of Results Pilot Projects Monitoring, Intraoperative Treatment Outcome Machine Learning Software Algorithms Inflammatory Bowel Diseases Patient Compliance Patient Readmission Medical Informatics Colorectal Surgery Infusions, Intravenous Ketorolac Humans Data Interpretation, Statistical Artificial Intelligence Signal Processing, Computer-Assisted Colonic Neoplasms
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Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches.

Journal of healthcare engineering Sep 23, 2018
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime import...
Humans Thyroid Gland Automation Image Processing, Computer-Assisted Software Thyroid Neoplasms Neural Networks, Computer Decision Trees Algorithms Ultrasonography Machine Learning Reproducibility of Results Imaging, Three-Dimensional Diagnosis, Computer-Assisted
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