AIMC Topic: Decision Trees

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Application of supervised machine learning algorithms in the classification of sagittal gait patterns of cerebral palsy children with spastic diplegia.

Computers in biology and medicine Jan 16, 2019
Gait classification has been widely used for children with cerebral palsy (CP) to assist with clinical decision making and to evaluate different treatment outcomes. The aim of this study was to evaluate supervised machine learning algorithms in the c...
Child Support Vector Machine Decision Trees Gait Cerebral Palsy Humans Neural Networks, Computer Female Male
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Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

Medical physics Dec 28, 2018
PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., random forests) and single-model methods (e.g., logistic regression and decision trees) in predictive modeling of post-RT treatment failure and adverse eve...
Decision Trees Predictive Value of Tests Data Mining Humans Radiotherapy Dosage Machine Learning Electronic Health Records Female Breast Neoplasms Middle Aged Treatment Outcome
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The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining.

International journal of medical informatics Dec 27, 2018
BACKGROUND: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the disease. It is believed that new data analysis methods may be applied to this disease, and this may be...
Heart Diseases Rheumatic Fever Humans Algorithms Child, Preschool Decision Trees Female Child Bayes Theorem Male Data Mining Adolescent
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Using Lexical Chains to Identify Text Difficulty: A Corpus Statistics and Classification Study.

IEEE journal of biomedical and health informatics Dec 6, 2018
Our goal is data-driven discovery of features for text simplification. In this paper, we investigate three types of lexical chains: exact, synonymous, and semantic. A lexical chain links semantically related words in a document. We examine their pote...
Decision Trees Natural Language Processing Bayes Theorem Databases, Factual Medical Informatics Semantics Logistic Models Support Vector Machine Consumer Health Information
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Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely uns...
Bayes Theorem Semantics Logistic Models Support Vector Machine Decision Trees Natural Language Processing Humans Algorithms
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Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis), without other liver diseases and without excessive alcohol consumption. NAFLD consists of a spectr...
Alanine Transaminase Aspartate Aminotransferases Liver Function Tests Decision Trees Disease Progression Risk Factors Supervised Machine Learning Humans Case-Control Studies Aged Non-alcoholic Fatty Liver Disease Fatty Liver Cohort Studies Male Biomarkers Hepatitis Logistic Models Middle Aged Diabetes Mellitus, Type 2 Electronic Health Records Liver Cirrhosis Female Health Status
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Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.

PloS one Dec 4, 2018
OBJECTIVE: Limited evidences are available on biomarkers to recognize Systemic Lupus erythematosus (SLE) patients at risk to develop erosive arthritis. Anti-citrullinated peptide antibodies (ACPA) have been widely investigated and identified in up to...
Humans Machine Learning Risk Factors Adult Cross-Sectional Studies Biomarkers Female Autoantibodies Logistic Models Rheumatoid Factor Male Anti-Citrullinated Protein Antibodies Arthritis Decision Trees Middle Aged Protein Carbamylation Lupus Erythematosus, Systemic Cohort Studies Ultrasonography
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Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.

PloS one Nov 9, 2018
BACKGROUND: The purpose of this study was to build a model of machine learning (ML) for the prediction of mortality in patients with isolated moderate and severe traumatic brain injury (TBI).
Brain Injuries, Traumatic Decision Trees Middle Aged Taiwan ROC Curve Predictive Value of Tests Machine Learning Bayes Theorem Logistic Models Aged, 80 and over Abbreviated Injury Scale Female Support Vector Machine Young Adult Humans Adult Aged Neural Networks, Computer Male
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Boosted feature selectors: a case study on prediction P-gp inhibitors and substrates.

Journal of computer-aided molecular design Oct 26, 2018
Feature selection is commonly used as a preprocessing step to machine learning for improving learning performance, lowering computational complexity and facilitating model interpretation. This paper proposes the application of boosting feature select...
Quantitative Structure-Activity Relationship ATP Binding Cassette Transporter, Subfamily B Support Vector Machine Decision Trees Molecular Structure Ligands Machine Learning Algorithms Protein Binding
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JOURNAL CLUB: Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information.

AJR. American journal of roentgenology Oct 24, 2018
OBJECTIVE: When treatment decisions are being made for patients with acute ischemic stroke, timely and accurate outcome prediction plays an important role. The optimal rehabilitation strategy also relies on long-term outcome predictions. The decision...
Humans Machine Learning Tomography, X-Ray Computed Female Male Middle Aged Decision Trees Algorithms Biomarkers Prognosis Retrospective Studies Demography Predictive Value of Tests Stroke Brain Ischemia Computed Tomography Angiography
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