AIMC Topic: Support Vector Machine

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Quantitative analysis of yeast fermentation process using Raman spectroscopy: Comparison of CARS and VCPA for variable selection.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Nov 11, 2019
Yeast is one of the most widely used microbial species in the field of microbiology, and it is crucial that rapid and accurate monitoring of its process. Therefore, this study presents a method using Raman spectroscopy for quantitative analysis of ye...
Fermentation Saccharomyces cerevisiae Spectroscopy, Near-Infrared Spectrum Analysis, Raman Support Vector Machine Models, Biological
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Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses Nov 11, 2019
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...
Middle Aged Diagnosis, Computer-Assisted Support Vector Machine Cluster Analysis Parkinson Disease Humans Female Pattern Recognition, Automated Neural Networks, Computer Reproducibility of Results Models, Statistical False Positive Reactions Machine Learning Aged Principal Component Analysis Algorithms Male Gait Acoustics
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Input representations and classification strategies for automated human gait analysis.

Gait & posture Nov 9, 2019
BACKGROUND: Quantitative gait analysis produces a vast amount of data, which can be difficult to analyze. Automated gait classification based on machine learning techniques bear the potential to support clinicians in comprehending these complex data....
Principal Component Analysis Gait Gait Analysis Gait Disorders, Neurologic Humans Young Adult Support Vector Machine
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A predictive analytics framework for identifying patients at risk of developing multiple medical complications caused by chronic diseases.

Artificial intelligence in medicine Nov 9, 2019
Chronic diseases often cause several medical complications. This paper aims to predict multiple complications among patients with a chronic disease. The literature uses single-task learning algorithms to predict complications independently and assume...
Chronic Disease Humans Machine Learning Algorithms Risk Factors Support Vector Machine
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Prediction of pulmonary pressure after Glenn shunts by computed tomography-based machine learning models.

European radiology Nov 8, 2019
OBJECTIVES: This study aimed to develop non-invasive machine learning classifiers for predicting post-Glenn shunt patients with low and high risks of a mean pulmonary arterial pressure (mPAP) > 15 mmHg based on preoperative cardiac computed tomograph...
Fontan Procedure Heart Defects, Congenital Pulmonary Atresia Tricuspid Atresia Cardiac Catheterization Blood Pressure Bayes Theorem Discriminant Analysis Double Outlet Right Ventricle Transposition of Great Vessels Pulmonary Artery Heart Septal Defects Univentricular Heart Young Adult Male Infant Lung Adolescent Child, Preschool Child Logistic Models Support Vector Machine Algorithms Prognosis Retrospective Studies Tomography, X-Ray Computed Female Humans Machine Learning
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Artificial plant optimization algorithm to detect heart rate & presence of heart disease using machine learning.

Artificial intelligence in medicine Nov 8, 2019
In today's world, cardiovascular diseases are prevalent becoming the leading cause of death; more than half of the cardiovascular diseases are due to Coronary Heart Disease (CHD) which generates the demand of predicting them timely so that people can...
Heart Diseases Databases, Factual Heart Rate Support Vector Machine Coronary Disease Predictive Value of Tests Humans Photosynthesis Plethysmography Plants Artificial Intelligence Programming Languages Machine Learning Algorithms
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Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods.

Environmental science and pollution research international Nov 7, 2019
Difenoconazole is a fungicide extensively used in agriculture. The aim of this study was to evaluate the effects of difenoconazole fungicide on the sperm quality of rats. Wistar rats were divided into four groups: control and exposed to 5 (D5), 10 (D...
Machine Learning Animals Male Rats, Wistar Rats Spermatozoa Sperm Count Fungicides, Industrial Dioxolanes Sperm Motility Epididymis Triazoles Spectrum Analysis, Raman Toxicity Tests Support Vector Machine Testis DNA Damage
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Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.

European journal of radiology Nov 6, 2019
PURPOSE: To evaluate the performance of machine learning (ML)-based computed tomography (CT) radiomics analysis for discriminating between low grade (WHO/ISUP I-II) and high grade (WHO/ISUP III-IV) clear cell renal cell carcinomas (ccRCCs).
Humans Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Predictive Value of Tests Reproducibility of Results Neoplasm Grading Aged Middle Aged Image Interpretation, Computer-Assisted Aged, 80 and over Kidney Kidney Neoplasms Carcinoma, Renal Cell Young Adult Logistic Models Adult Support Vector Machine Male Diagnosis, Differential
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A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.

BMC medical informatics and decision making Nov 6, 2019
BACKGROUND: Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of mach...
Support Vector Machine Predictive Value of Tests ROC Curve Humans Machine Learning Logistic Models Electronic Health Records Nutrition Surveys Female Diabetes Mellitus Male Cardiovascular Diseases
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A machine-learning approach to predict postprandial hypoglycemia.

BMC medical informatics and decision making Nov 6, 2019
BACKGROUND: For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While there have been many studies...
Humans Machine Learning Algorithms Logistic Models Hypoglycemic Agents Retrospective Studies Support Vector Machine Adult Hypoglycemia Sensitivity and Specificity Blood Glucose Self-Monitoring Blood Glucose
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