AIMC Topic: Machine Learning

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Using machine learning methods for predicting inhospital mortality in patients undergoing open repair of abdominal aortic aneurysm.

Journal of biomedical informatics Jul 6, 2016
An abdominal aortic aneurysm is an abnormal dilatation of the aortic vessel at abdominal level. This disease presents high rate of mortality and complications causing a decrease in the quality of life and increasing the cost of treatment. To estimate...
Machine Learning Risk Factors Risk Assessment Humans Aortic Aneurysm, Abdominal Bayes Theorem Quality of Life Hospital Mortality Treatment Outcome
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Image analysis and machine learning in digital pathology: Challenges and opportunities.

Medical image analysis Jul 4, 2016
With the rise in whole slide scanner technology, large numbers of tissue slides are being scanned and represented and archived digitally. While digital pathology has substantial implications for telepathology, second opinions, and education there are...
Telepathology Humans Machine Learning Precision Medicine Image Processing, Computer-Assisted Radiology Pathology
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Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

Australasian physical & engineering sciences in medicine Jul 4, 2016
Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine contro...
Humans Brain-Computer Interfaces Task Performance and Analysis Support Vector Machine Principal Component Analysis Least-Squares Analysis Electroencephalography Signal Processing, Computer-Assisted Pattern Recognition, Automated Female Neural Networks, Computer Adult Machine Learning Male
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The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins.

Database : the journal of biological databases and curation Jul 3, 2016
Genomics, epigenomics, transcriptomics, proteomics and metabolomics efforts rapidly generate a plethora of data on the activity and levels of biomolecules within mammalian cells. At the same time, curation projects that organize knowledge from the bi...
Humans Animals Mice Machine Learning Databases, Protein Data Mining Databases, Nucleic Acid
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Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015).

Journal of chemical information and modeling Jul 1, 2016
The renewed urgency to develop new treatments for Mycobacterium tuberculosis (Mtb) infection has resulted in large-scale phenotypic screening and thousands of new active compounds in vitro. The next challenge is to identify candidates to pursue in a ...
Machine Learning Animals Drug Discovery Bayes Theorem Tuberculosis Mycobacterium tuberculosis Mice Computational Biology Disease Models, Animal
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Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.

PloS one Jul 1, 2016
A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps...
Pattern Recognition, Automated Machine Learning Fisheries Animals Data Mining Spacecraft
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Machine Learning Techniques in Clinical Vision Sciences.

Current eye research Jun 30, 2016
This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and tr...
Eye Diseases Humans Sensitivity and Specificity Vision, Ocular Machine Learning Monitoring, Physiologic Diagnostic Techniques, Ophthalmological Algorithms Multimodal Imaging
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Combining machine learning and matching techniques to improve causal inference in program evaluation.

Journal of evaluation in clinical practice Jun 29, 2016
RATIONALE, AIMS AND OBJECTIVES: Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balan...
Humans Machine Learning Algorithms Female Discriminant Analysis Program Evaluation Middle Aged Adult Causality Random Allocation Male Chronic Disease Propensity Score
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Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

Health informatics journal Jun 27, 2016
This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set...
Gene Expression Hodgkin Disease Prognosis Cluster Analysis Decision Trees Humans Machine Learning
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Prediction of bacterial associations with plants using a supervised machine-learning approach.

Environmental microbiology Jun 27, 2016
Recent scenarios of fresh produce contamination by human enteric pathogens have resulted in severe food-borne outbreaks, and a new paradigm has emerged stating that some human-associated bacteria can use plants as secondary hosts. As a consequence, t...
Plants Fruit Vegetables Bacteria Foodborne Diseases Humans Machine Learning
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