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A comparison of machine learning and logistic regression in modelling the association of body condition score and submission rate.

Preventive veterinary medicine Aug 31, 2019
The effect of body condition score (BCS) on reproductive outcomes is complex, dynamic and non-linear with interaction and confounding. The flexibility inherent in machine learning algorithms makes them attractive for analysing complex data. This stud...
Decision Trees New Zealand Models, Biological Lactation Animals Cattle ROC Curve Logistic Models Reproduction Breeding Dairying Body Constitution Machine Learning Algorithms Female
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A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissection.

BJU international Aug 28, 2019
OBJECTIVES: To develop a machine learning (ML)-assisted model to identify candidates for extended pelvic lymph node dissection (ePLND) in prostate cancer by integrating clinical, biopsy, and precisely defined magnetic resonance imaging (MRI) findings...
Prostate Pelvis Aged, 80 and over Humans Male Support Vector Machine Machine Learning Lymph Node Excision Middle Aged Magnetic Resonance Imaging Retrospective Studies Decision Trees Lymph Nodes Aged Prostatic Neoplasms
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Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.

International journal of medical informatics Aug 24, 2019
INTRODUCTION: Machine learning has been increasingly used to develop predictive models to diagnose different disease conditions. The heterogeneity of the kidney transplant population makes predicting graft outcomes extremely challenging. Several kidn...
Humans Neural Networks, Computer Machine Learning Kidney Transplantation Databases, Factual Decision Trees Predictive Value of Tests Graft Rejection Bayes Theorem
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Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

Artificial intelligence in medicine Aug 9, 2019
INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learnin...
Depression Decision Trees Models, Biological Schizophrenia Data Mining Machine Learning Alzheimer Disease Mental Disorders Psychiatry Precision Medicine Humans Artificial Intelligence
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Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.

Research synthesis methods Aug 5, 2019
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free s...
Algorithms Research Design Biology Reproducibility of Results Ecology Models, Statistical Animals Asia Artificial Intelligence Decision Trees Geography Ecosystem Data Interpretation, Statistical Introduced Species Machine Learning Review Literature as Topic
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Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).

Journal of biomedical informatics Jul 30, 2019
AIM: The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical softwa...
Prospective Studies Area Under Curve Humans Support Vector Machine Supervised Machine Learning Risk Factors Coronary Disease Longitudinal Studies Neural Networks, Computer Computational Biology Models, Statistical Algorithms Logistic Models Decision Trees Databases, Factual
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Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification.

Molecules (Basel, Switzerland) Jul 26, 2019
Efficient identification of chemical probes for the manipulation and understanding of biological systems demands specificity for target proteins. Computational means to optimize candidate compound selection for experimental selectivity evaluation are...
Databases, Chemical Quantitative Structure-Activity Relationship Machine Learning Algorithms Models, Theoretical Decision Support Techniques Decision Trees Reproducibility of Results Ligands Drug Discovery Chemical Phenomena Computational Biology
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Machine learning and statistical models for predicting indoor air quality.

Indoor air Jul 25, 2019
Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mo...
Air Pollutants Air Pollution, Indoor Humans Neural Networks, Computer Models, Statistical Machine Learning Regression Analysis Environmental Monitoring Decision Trees
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Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.

International journal of environmental research and public health Jul 25, 2019
Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but their combined impact on hypercholesterolemia (HC) is poorly understood. The aim of this study was to compare the performance of various machine learning ...
Humans Machine Learning Female Adult Forecasting Cadmium Male Republic of Korea Hypercholesterolemia Lead Middle Aged Decision Trees ROC Curve Environmental Pollutants Logistic Models Environmental Exposure Support Vector Machine Mercury
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Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.

Artificial intelligence in medicine Jul 25, 2019
OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical development and future health. As per the World Health Organization, India has the highest number of pre-term births [1], with over 3.5 million babies born...
Decision Trees Birth Weight Heart Rate Datasets as Topic Intensive Care Units, Neonatal Clinical Decision Rules Infant, Extremely Premature Humans Infant, Premature Apnea Deep Learning Neural Networks, Computer Gestational Age India Algorithms Support Vector Machine Infant, Newborn
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