AIMC Topic: Reproducibility of Results

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[Artificial intelligence in medicine: limits and obstacles.].

Recenti progressi in medicina
Data scientists and physicians are starting to use artificial intelligence (AI) even in the medical field in order to better understand the relationships among the huge amount of data coming from the great number of sources today available. Through t...

Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects.

Journal of glaucoma
PURPOSE: Existing summary statistics based upon optical coherence tomographic (OCT) scans and/or visual fields (VFs) are suboptimal for distinguishing between healthy and glaucomatous eyes in the clinic. This study evaluates the extent to which a hyb...

Editor's Highlight: Identification of Any Structure-Specific Hepatotoxic Potential of Different Pyrrolizidine Alkaloids Using Random Forests and Artificial Neural Networks.

Toxicological sciences : an official journal of the Society of Toxicology
Pyrrolizidine alkaloids (PAs) are characteristic metabolites of some plant families and form a powerful defense mechanism against herbivores. More than 600 different PAs are known. PAs are ester alkaloids composed of a necine base and a necic acid, w...

Intravoxel Incoherent Motion: Model-Free Determination of Tissue Type in Abdominal Organs Using Machine Learning.

Investigative radiology
PURPOSE: For diffusion data sets including low and high b-values, the intravoxel incoherent motion model is commonly applied to characterize tissue. The aim of the present study was to show that machine learning allows a model-free approach to determ...

Computer-Aided Diagnosis of Lung Nodules in Computed Tomography by Using Phylogenetic Diversity, Genetic Algorithm, and SVM.

Journal of digital imaging
Lung cancer is pointed as the major cause of death among patients with cancer throughout the world. This work is intended to develop a methodology for diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resour...

DeepPhe: A Natural Language Processing System for Extracting Cancer Phenotypes from Clinical Records.

Cancer research
Precise phenotype information is needed to understand the effects of genetic and epigenetic changes on tumor behavior and responsiveness. Extraction and representation of cancer phenotypes is currently mostly performed manually, making it difficult t...

Gating mass cytometry data by deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Mass cytometry or CyTOF is an emerging technology for high-dimensional multiparameter single cell analysis that overcomes many limitations of fluorescence-based flow cytometry. New methods for analyzing CyTOF data attempt to improve autom...

Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks.

JAMA ophthalmology
IMPORTANCE: Age-related macular degeneration (AMD) affects millions of people throughout the world. The intermediate stage may go undetected, as it typically is asymptomatic. However, the preferred practice patterns for AMD recommend identifying indi...

Neural networks as a tool to predict syncope risk in the Emergency Department.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying ...