AIMC Topic: Principal Component Analysis

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Classification of Chicken Parts Using a Portable Near-Infrared (NIR) Spectrophotometer and Machine Learning.

Applied spectroscopy Jul 31, 2018
Identification of different chicken parts using portable equipment could provide useful information for the processing industry and also for authentication purposes. Traditionally, physical-chemical analysis could deal with this task, but some disadv...
Poultry Products Fats Poultry Proteins Spectroscopy, Near-Infrared Chickens Principal Component Analysis Machine Learning Algorithms Animals
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Using principal component analysis to reduce complex datasets produced by robotic technology in healthy participants.

Journal of neuroengineering and rehabilitation Jul 31, 2018
BACKGROUND: The KINARM robot produces a granular dataset of participant performance metrics associated with proprioceptive, motor, visuospatial, and executive function. This comprehensive battery includes several behavioral tasks that each generate 9...
Robotics Healthy Volunteers Proprioception Adult Male Principal Component Analysis Humans Female
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Study on Contribution of Biological Interpretable and Computer-Aided Features Towards the Classification of Childhood Medulloblastoma Cells.

Journal of medical systems Jul 4, 2018
Diagnosis and Prognosis of brain tumour in children is always a critical case. Medulloblastoma is that subtype of brain tumour which occurs most frequently amongst children. Post-operation, the classification of its subtype is most vital for further ...
Support Vector Machine Humans Principal Component Analysis Cerebellar Neoplasms Algorithms Medulloblastoma Child
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Identification of cervical cancer using laser-induced breakdown spectroscopy coupled with principal component analysis and support vector machine.

Lasers in medical science Jun 26, 2018
Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interpretation of biopsy material. In this work, laser-induced breakdown spectroscopy (LIBS) was used in c...
Elements Principal Component Analysis Spectrum Analysis Lasers Female Uterine Cervical Neoplasms Support Vector Machine Humans
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Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

Neuron Jun 7, 2018
Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it rema...
Animals Prefrontal Cortex Time Factors Neural Networks, Computer Brain-Computer Interfaces Motor Cortex Macaca mulatta Mice Unsupervised Machine Learning Principal Component Analysis Spatial Navigation
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C-PUGP: A cluster-based positive unlabeled learning method for disease gene prediction and prioritization.

Computational biology and chemistry Jun 1, 2018
Disease gene detection is an important stage in the understanding disease processes and treatment. Some candidate disease genes are identified using many machine learning methods Although there are some differences in these methods including feature ...
Disease Genes Machine Learning Genomics Genetic Predisposition to Disease Principal Component Analysis Mutation
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Host Cell Prediction of Exosomes Using Morphological Features on Solid Surfaces Analyzed by Machine Learning.

The journal of physical chemistry. B May 31, 2018
Exosomes are extracellular nanovesicles released from any cells and found in any body fluid. Because exosomes exhibit information of their host cells (secreting cells), their analysis is expected to be a powerful tool for early diagnosis of cancers. ...
Support Vector Machine Principal Component Analysis Silicon Dioxide Microscopy, Atomic Force Humans Titanium Cell Line, Tumor Exosomes
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Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BMC cancer May 30, 2018
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...
Staining and Labeling Predictive Value of Tests Principal Component Analysis Neoplasm Staging Genetic Testing Breast Middle Aged ROC Curve Image Processing, Computer-Assisted Young Adult Adult Female Breast Neoplasms Risk Factors Receptors, Estrogen Aged Models, Biological Humans Supervised Machine Learning Prognosis Cell Nucleus
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Managing the 1920s' Chilean educational crisis: A historical view combined with machine learning.

PloS one May 30, 2018
In the first decades of the 20th century, political actors diagnosed the incubation of a crisis in the Chilean schooling process. Low rates of enrollment, literacy, and attendance, inefficiency in the use of resources, poverty, and a reduced number o...
Chile Cluster Analysis Machine Learning Geography Databases as Topic Decision Trees Algorithms Education History, 20th Century Principal Component Analysis Reproducibility of Results
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Microaneurysm Detection Using Principal Component Analysis and Machine Learning Methods.

IEEE transactions on nanobioscience May 24, 2018
Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR. In th...
Support Vector Machine Principal Component Analysis Microaneurysm Humans Diabetic Retinopathy Image Interpretation, Computer-Assisted Neural Networks, Computer Machine Learning
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