AIMC Topic: Machine Learning

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Predicting vital sign deterioration with artificial intelligence or machine learning.

Journal of clinical monitoring and computing Jun 28, 2019
Artificial Intelligence Machine Learning Intensive Care Units Tachycardia Humans
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Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

European journal of radiology Jun 28, 2019
PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier to predict the cell proliferation(Ki-67)in non-small cell lung cancer (NSCLC).
Aged, 80 and over Retrospective Studies Adult Cell Proliferation Tomography, X-Ray Computed Sensitivity and Specificity Humans Middle Aged Female Lung Male Machine Learning Aged ROC Curve Carcinoma, Non-Small-Cell Lung Algorithms Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted
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Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease.

Computers in biology and medicine Jun 28, 2019
BACKGROUND: Given the increasing recognition of the significance of non-motor symptoms in Parkinson's disease, we investigate the optimal use of machine learning methods for the prediction of the Montreal Cognitive Assessment (MoCA) score at year 4 f...
Models, Statistical Humans Mental Status and Dementia Tests Machine Learning Algorithms Female Middle Aged Disease Progression Longitudinal Studies Parkinson Disease Aged Aged, 80 and over Adult Male
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Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Journal of chemical information and modeling Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
Reproducibility of Results Models, Biological Machine Learning Animals Gene Expression Regulation Rats Chemical and Drug Induced Liver Injury Algorithms Male Rats, Sprague-Dawley Vinblastine Computer Simulation Drug Discovery Structure-Activity Relationship Molecular Structure
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Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

Journal of medical systems Jun 28, 2019
This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques. Thirty COPD and 25 healthy subject data are recorded. Total of 39 lung sound features and 3 spirome...
Humans Machine Learning Algorithms Female Pulmonary Disease, Chronic Obstructive Sensitivity and Specificity Male Risk Assessment Logistic Models Vital Capacity Support Vector Machine Forced Expiratory Volume Respiratory Sounds Spirometry
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A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization.

Journal of medical systems Jun 28, 2019
The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in those patients presenting early-stage angina-like symptom using machine learning algorithms. We obtained data from 2344 ACS patients, who required revasc...
Algorithms ROC Curve Female Humans Predictive Value of Tests Male Machine Learning Acute Coronary Syndrome Risk Assessment Myocardial Revascularization
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Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters.

Environmental monitoring and assessment Jun 28, 2019
Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia (ragweed) is known for its abundant production of pollen and its potent allergic effect in Nort...
Hypersensitivity Radar Plant Extracts Environmental Monitoring Weather Antigens, Plant Humans Machine Learning Forecasting
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Using machine learning to examine the relationship between asthma and absenteeism.

Environmental monitoring and assessment Jun 28, 2019
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating ...
Environmental Health Academic Success Absenteeism Adolescent Child Schools Texas Humans Machine Learning Female Asthma Male Students
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Using machine learning to understand the temporal morphology of the PM annual cycle in East Asia.

Environmental monitoring and assessment Jun 28, 2019
PM air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have been established over the last decade to monitor real-time PM concentration. However, even thi...
Humans Air Pollution Particulate Matter Linear Models Asia, Eastern Machine Learning Algorithms Environmental Monitoring Air Pollutants
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A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Nature communications Jun 28, 2019
Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be supe...
Organoids Glioblastoma Gene Expression Regulation Female Promoter Regions, Genetic Cell Separation Breast Neoplasms Humans Lentivirus Gene Library Cell Line, Tumor Machine Learning Regulatory Elements, Transcriptional Neoplastic Stem Cells Software Induced Pluripotent Stem Cells
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