AIMC Topic: Reproducibility of Results

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Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds.

Plant physiology Oct 7, 2019
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary...
Machine Learning Algorithms Phenotype Reproducibility of Results Nicotiana Plants Plant Stems Plant Shoots Environment Imaging, Three-Dimensional Plant Leaves Plant Roots Solanum lycopersicum
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Democratized image analytics by visual programming through integration of deep models and small-scale machine learning.

Nature communications Oct 7, 2019
Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we us...
Green Fluorescent Proteins Mice, Transgenic Saccharomyces cerevisiae Proteins Dictyostelium Internet Life Cycle Stages Oocytes Saccharomyces cerevisiae Reproducibility of Results Animals Image Processing, Computer-Assisted Computational Biology Neural Networks, Computer Machine Learning
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Machine learning in cardiovascular magnetic resonance: basic concepts and applications.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Oct 7, 2019
Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improvi...
Myocardial Perfusion Imaging Magnetic Resonance Imaging, Cine Humans Myocardium Machine Learning Supervised Machine Learning Reproducibility of Results Cardiovascular Diseases Deep Learning Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Unsupervised Machine Learning Coronary Circulation Predictive Value of Tests
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QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.

G3 (Bethesda, Md.) Oct 7, 2019
Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine ma...
Machine Learning Software Algorithms Quantitative Trait Loci Genes, Plant Quantitative Trait, Heritable Web Browser Arabidopsis Reproducibility of Results ROC Curve Computational Biology Oryza
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Computer-aided diagnosis of laryngeal cancer via deep learning based on laryngoscopic images.

EBioMedicine Oct 5, 2019
OBJECTIVE: To develop a deep convolutional neural network (DCNN) that can automatically detect laryngeal cancer (LCA) in laryngoscopic images.
Humans Reproducibility of Results Sensitivity and Specificity Laryngoscopy Laryngeal Neoplasms Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Models, Theoretical
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Predicting likelihood of psychological disorders in PlayerUnknown's Battlegrounds (PUBG) players from Asian countries using supervised machine learning.

Addictive behaviors Oct 4, 2019
Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies have exhibited that excessive engagement in games can lead to Internet Gaming Disorder (IGD). Internet ...
Self Concept Supervised Machine Learning Asia Internet Addiction Disorder Adult Humans Male Female Surveys and Questionnaires Reproducibility of Results Adolescent Young Adult
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Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural network.

Computer methods and programs in biomedicine Oct 4, 2019
BACKGROUND AND OBJECTIVE: We investigated a novel method using a 2D convolutional neural network (CNN) to identify superior and inferior vertebrae in a single slice of CT images, and a post-processing for 3D segmentation and separation of cervical ve...
Automation Case-Control Studies Image Processing, Computer-Assisted Cervical Vertebrae Datasets as Topic Humans Neural Networks, Computer Tomography, X-Ray Computed Reproducibility of Results
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ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Scientific reports Oct 4, 2019
Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely a...
Pathology, Clinical Colorectal Neoplasms Colon Humans Deep Learning Reproducibility of Results Image Processing, Computer-Assisted Bayes Theorem Rectum Workflow Uncertainty
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Potential of automatic diagnosis system with linked color imaging for diagnosis of Helicobacter pylori infection.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Oct 2, 2019
BACKGROUND AND AIM: It is necessary to establish universal methods for endoscopic diagnosis of Helicobacter pylori (HP) infection, such as computer-aided diagnosis. In the present study, we propose a multistage diagnosis algorithm for HP infection.
Helicobacter pylori Clinical Competence Support Vector Machine Predictive Value of Tests Helicobacter Infections Reproducibility of Results Aged Aged, 80 and over Endoscopy Adult Humans Male Retrospective Studies Middle Aged Female Diagnosis, Computer-Assisted
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Endoscopic detection and differentiation of esophageal lesions using a deep neural network.

Gastrointestinal endoscopy Oct 1, 2019
BACKGROUND AND AIMS: Diagnosing esophageal squamous cell carcinoma (SCC) depends on individual physician expertise and may be subject to interobserver variability. Therefore, we developed a computerized image-analysis system to detect and differentia...
Reproducibility of Results Aged Aged, 80 and over Adult Humans Neural Networks, Computer Female Image Processing, Computer-Assisted Neoplasm Invasiveness Esophagus Esophageal Neoplasms Observer Variation Sensitivity and Specificity Male Middle Aged Deep Learning Narrow Band Imaging Precancerous Conditions Optical Imaging Esophageal Squamous Cell Carcinoma Esophageal Diseases
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