AIMC Topic: Machine Learning

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Artificial intelligence method to classify ophthalmic emergency severity based on symptoms: a validation study.

BMJ open Jul 5, 2020
OBJECTIVES: We investigated the usefulness of machine learning artificial intelligence (AI) in classifying the severity of ophthalmic emergency for timely hospital visits.
Machine Learning Algorithms Retrospective Studies Emergency Service, Hospital Humans
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Trace elements and machine learning for Brazilian beef traceability.

Food chemistry Jul 4, 2020
Brazilian livestock with a herd of more than 215 million animals is distributed over a vast area of 160 million hectares, leading the country to the first position in the world beef exports and second in beef production and consumption. Animals risen...
Red Meat Neural Networks, Computer Ecosystem Machine Learning Brazil Animals Trace Elements Cattle
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Stability assessment of extracts obtained from Arbutus unedo L. fruits in powder and solution systems using machine-learning methodologies.

Food chemistry Jul 4, 2020
Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially flavan-3-ols (catechin, gallocatechin, among others). The interest of flavan-3-ols has increased due their bioactive actions, namely antioxidant and ...
Hydrogen-Ion Concentration Fruit Food Preservatives Temperature Food Storage Powders Flavonoids Solutions Catechin Neural Networks, Computer Antioxidants Kinetics Ericaceae Plant Extracts Support Vector Machine Machine Learning
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Ischemia and outcome prediction by cardiac CT based machine learning.

The international journal of cardiovascular imaging Jul 4, 2020
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for card...
Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Prognosis Reproducibility of Results Risk Assessment Plaque, Atherosclerotic Vascular Calcification Computed Tomography Angiography Coronary Artery Disease Heart Disease Risk Factors Coronary Vessels Humans Machine Learning
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Personalized connectome fingerprints: Their importance in cognition from childhood to adult years.

NeuroImage Jul 4, 2020
Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a pe...
Cognition Magnetic Resonance Imaging Intelligence Neuroimaging White Matter Nerve Net Human Development Male Middle Aged Infant Child, Preschool Humans Aged Young Adult Machine Learning Adult Learning Female
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Responses to the letter on "Transfer learning for neural network model in Chlorophyll-a dynamics prediction".

Environmental science and pollution research international Jul 4, 2020
Neural Networks, Computer Machine Learning Learning Chlorophyll Chlorophyll A
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Classification of pachychoroid disease on ultrawide-field indocyanine green angiography using auto-machine learning platform.

The British journal of ophthalmology Jul 3, 2020
AIMS: Automatic identification of pachychoroid maybe used as an adjunctive method to confirm the condition and be of help in treatment for macular diseases. This study investigated the feasibility of classifying pachychoroid disease on ultra-widefiel...
Retinal Pigment Epithelium Choroid Diseases Coloring Agents Indocyanine Green Female Humans Fluorescein Angiography Middle Aged Aged Machine Learning Male Follow-Up Studies Retrospective Studies Tomography, Optical Coherence Fundus Oculi
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Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints.

Toxicology letters Jul 3, 2020
The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug develop...
Potassium Channel Blockers ERG1 Potassium Channel CHO Cells Models, Molecular Cricetulus Humans Databases, Factual Cricetinae Area Under Curve Machine Learning Animals Peptide Mapping Algorithms Cardiotoxicity Support Vector Machine Predictive Value of Tests
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An ensemble learning based hybrid model and framework for air pollution forecasting.

Environmental science and pollution research international Jul 3, 2020
As advance of economy and industry, the impact of air pollution has gradually gained attention. In order to predict air quality, there were many studies that exploited various machine learning techniques to build predictive model for pollutant concen...
Neural Networks, Computer Air Pollution Machine Learning Forecasting Environmental Monitoring
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Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture Jul 3, 2020
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...
Machine Learning Algorithms Stress, Physiological Quantitative Trait Loci Droughts Plant Breeding Phenotype Genotype Seeds Fabaceae
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