AIMC Topic: Machine Learning

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Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.

Translational psychiatry Mar 21, 2017
To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the comp...
Humans Hydrocortisone Machine Learning Saliva Algorithms Lymphocytes Female Heart Rate Young Adult Adrenocorticotropic Hormone Adult Male Risk Assessment Longitudinal Studies Linear Models Stress Disorders, Post-Traumatic Blood Pressure Urine ROC Curve Area Under Curve Wounds and Injuries Support Vector Machine Emergency Service, Hospital Psychological Trauma Norepinephrine Receptors, Glucocorticoid
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Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification.

The international journal of cardiovascular imaging Mar 20, 2017
The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to...
Myocardial Contraction Magnetic Resonance Imaging Predictive Value of Tests Principal Component Analysis Myocardial Infarction Image Interpretation, Computer-Assisted Observer Variation Automation Pattern Recognition, Automated Ventricular Function, Left Echocardiography, Doppler, Color Severity of Illness Index Case-Control Studies Diagnosis, Computer-Assisted Time Factors Humans Machine Learning Reproducibility of Results Biomechanical Phenomena
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MRF-ANN: a machine learning approach for automated ER scoring of breast cancer immunohistochemical images.

Journal of microscopy Mar 20, 2017
Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the r...
Automation, Laboratory Female Breast Neoplasms Biomarkers, Tumor Image Processing, Computer-Assisted Humans Neural Networks, Computer Machine Learning Immunohistochemistry Receptors, Estrogen
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Early prediction of radiotherapy-induced parotid shrinkage and toxicity based on CT radiomics and fuzzy classification.

Artificial intelligence in medicine Mar 18, 2017
MOTIVATION: Patients under radiotherapy for head-and-neck cancer often suffer of long-term xerostomia, and/or consistent shrinkage of parotid glands. In order to avoid these drawbacks, adaptive therapy can be planned for patients at risk, if the pred...
Cranial Irradiation Xerostomia Parotid Gland Early Diagnosis Radiotherapy Dosage Radiation Injuries Radiation Exposure Fuzzy Logic Predictive Value of Tests Bayes Theorem Radiographic Image Interpretation, Computer-Assisted Machine Learning Tomography, X-Ray Computed Risk Factors Time Factors Head and Neck Neoplasms Humans
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Prediction of high on-treatment platelet reactivity in clopidogrel-treated patients with acute coronary syndromes.

International journal of cardiology Mar 18, 2017
BACKGROUND: About 40% of clopidogrel-treated patients display high platelet reactivity (HPR). Alternative treatments of HPR patients, identified by platelet function tests, failed to improve their clinical outcomes in large randomized clinical trials...
Clopidogrel Platelet Activation Ticlopidine Female Aged Humans Male Gene Regulatory Networks Middle Aged Neural Networks, Computer Treatment Outcome Machine Learning Predictive Value of Tests Prospective Studies Acute Coronary Syndrome Platelet Aggregation Inhibitors
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Multitask Protein Function Prediction through Task Dissimilarity.

IEEE/ACM transactions on computational biology and bioinformatics Mar 17, 2017
Automated protein function prediction is a challenging problem with distinctive features, such as the hierarchical organization of protein functions and the scarcity of annotated proteins for most biological functions. We propose a multitask learning...
Machine Learning Algorithms Computational Biology Models, Statistical Proteins Humans Escherichia coli Proteins Drosophila Proteins Gene Ontology
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Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections.

Kidney international Mar 17, 2017
The immune system has evolved to sense invading pathogens, control infection, and restore tissue integrity. Despite symptomatic variability in patients, unequivocal evidence that an individual's immune system distinguishes between different organisms...
Biomarkers Female Reproducibility of Results Aged Aged, 80 and over Humans Machine Learning Gram-Negative Bacterial Infections Bacteria Peptide Mapping Predictive Value of Tests Peritonitis Area Under Curve Peritoneal Dialysis Middle Aged Acute Disease Case-Control Studies Adolescent Time Factors ROC Curve Young Adult Adult Male Point-of-Care Systems Point-of-Care Testing Nonlinear Dynamics Pattern Recognition, Automated Host-Pathogen Interactions Gram-Positive Bacterial Infections
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Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.

Annual review of clinical psychology Mar 17, 2017
Sensors in everyday devices, such as our phones, wearables, and computers, leave a stream of digital traces. Personal sensing refers to collecting and analyzing data from sensors embedded in the context of daily life with the aim of identifying human...
Neurophysiological Monitoring Humans Machine Learning Mental Disorders Telemedicine
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Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition.

Journal of chemical information and modeling Mar 17, 2017
The development of new antimalarial therapies is essential, and lowering the barrier of entry for the screening and discovery of new lead compound classes can spur drug development at organizations that may not have large compound screening libraries...
Models, Theoretical Bayes Theorem Malaria Antimalarials Quantitative Structure-Activity Relationship Machine Learning Temperature Drug Discovery ROC Curve
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Generating highly accurate prediction hypotheses through collaborative ensemble learning.

Scientific reports Mar 17, 2017
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosti...
Machine Learning Algorithms ROC Curve Models, Theoretical Area Under Curve Numerical Analysis, Computer-Assisted
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