AIMC Topic: Humans

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Chest Radiographs in Congestive Heart Failure: Visualizing Neural Network Learning.

Radiology Nov 6, 2018
Purpose To examine Generative Visual Rationales (GVRs) as a tool for visualizing neural network learning of chest radiograph features in congestive heart failure (CHF). Materials and Methods A total of 103 489 frontal chest radiographs in 46 712 pati...
Adult Male Middle Aged Infant Infant, Newborn Aged Aged, 80 and over Young Adult Radiographic Image Interpretation, Computer-Assisted Heart Failure Natriuretic Peptide, Brain Radiography, Thoracic Adolescent Child, Preschool Child ROC Curve Humans Neural Networks, Computer Databases, Factual Female Thorax
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A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using F-FDG PET of the Brain.

Radiology Nov 6, 2018
Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to t...
Fluorodeoxyglucose F18 Sensitivity and Specificity Male Middle Aged Deep Learning Retrospective Studies Cognitive Dysfunction Female Alzheimer Disease Aged Humans Positron-Emission Tomography Aged, 80 and over Algorithms Image Interpretation, Computer-Assisted
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Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.

Acta oncologica (Stockholm, Sweden) Nov 6, 2018
BACKGROUND: In this study, a deep convolutional neural network (CNN)-based automatic segmentation technique was applied to multiple organs at risk (OARs) depicted in computed tomography (CT) images of lung cancer patients, and the results were compar...
Image Processing, Computer-Assisted Lung Neoplasms Esophagus Spine Humans Neural Networks, Computer Tomography, X-Ray Computed Radiography, Thoracic Organs at Risk Radiography, Abdominal Radiotherapy Planning, Computer-Assisted Atlases as Topic Tumor Burden Anatomy, Artistic Pattern Recognition, Automated
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Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy.

Eye (London, England) Nov 6, 2018
Remarkable advances in biomedical research have led to the generation of large amounts of data. Using artificial intelligence, it has become possible to extract meaningful information from large volumes of data, in a shorter frame of time, with very ...
(1)
Humans Photography Deep Learning Diabetic Retinopathy ROC Curve Fundus Oculi Neural Networks, Computer Diagnostic Techniques, Ophthalmological Algorithms
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Editor's Note: Publication of AI Research in Radiology.

Radiology Nov 6, 2018
Research Editorial Policies Radiology Periodicals as Topic Humans Artificial Intelligence
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Safety of patient-facing digital symptom checkers.

Lancet (London, England) Nov 6, 2018
(3)
Quality of Health Care Humans Self Care Information Seeking Behavior Artificial Intelligence Diagnostic Errors Consumer Health Information Algorithms Triage Consumer Health Informatics Safety
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In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods.

Molecules (Basel, Switzerland) Nov 6, 2018
O⁶-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O⁶-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer r...
Quantitative Structure-Activity Relationship Antineoplastic Agents, Alkylating Apoptosis Linear Models Methyltransferases Humans Machine Learning Algorithms Animals
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Prediction of LncRNA Subcellular Localization with Deep Learning from Sequence Features.

Scientific reports Nov 6, 2018
Long non-coding RNAs are involved in biological processes throughout the cell including the nucleus, chromatin and cytosol. However, most lncRNAs remain unannotated and functional annotation of lncRNAs is difficult due to their low conservation and t...
Humans RNA, Long Noncoding Neural Networks, Computer Deep Learning Biological Transport Computational Biology Intracellular Space Sequence Analysis, RNA Cell Line
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Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Scientific reports Nov 6, 2018
Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishmen...
Humans Machine Learning Algorithms Databases, Factual Precision Medicine Female Biomarkers, Tumor Antimetabolites, Antineoplastic Ovarian Neoplasms Neoplasms Deoxycytidine Predictive Value of Tests Transcriptome Gemcitabine Fluorouracil Computational Biology Genome, Human Support Vector Machine
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Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms.

BMC ophthalmology Nov 6, 2018
BACKGROUND: Convolution neural networks have been considered for automatic analysis of fundus images to detect signs of diabetic retinopathy but suffer from low sensitivity.
Retinal Hemorrhage Microaneurysm Image Interpretation, Computer-Assisted Exudates and Transudates Diagnostic Techniques, Ophthalmological Humans Diabetic Retinopathy Neural Networks, Computer Sensitivity and Specificity Fundus Oculi
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