AIMC Topic:
Supervised Machine Learning

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Towards a Personal Health Record System for the Assesment and Monitoring of Sedentary Behavior in Indoor Locations.

Studies in health technology and informatics Jan 1, 2016
BACKGROUND: Sedentary behavior has been associated to the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Accelerometers and inclinometers have been used to estimate sedentary behavior...
Supervised Machine Learning Accelerometry Sedentary Behavior Algorithms Posture Humans Health Records, Personal Wireless Technology
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A Novel Teaching-Learning-Based Optimization for Improved Mutagenic Primer Design in Mismatch PCR-RFLP SNP Genotyping.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
Many single nucleotide polymorphisms (SNPs) for complex genetic diseases are genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in small-scale basic research studies. It is an essential work to design feasible ...
Computational Biology Supervised Machine Learning DNA Primers Polymerase Chain Reaction Polymorphism, Restriction Fragment Length Polymorphism, Single Nucleotide
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Multimodal manifold-regularized transfer learning for MCI conversion prediction.

Brain imaging and behavior Dec 1, 2015
As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk ...
Humans Aged Aged, 80 and over Middle Aged Databases, Factual Brain Prognosis Least-Squares Analysis Supervised Machine Learning ROC Curve Alzheimer Disease Magnetic Resonance Imaging Positron-Emission Tomography Multimodal Imaging Pattern Recognition, Automated Disease Progression Diagnosis, Computer-Assisted Cognitive Dysfunction
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Scaling up graph-based semisupervised learning via prototype vector machines.

IEEE transactions on neural networks and learning systems Mar 1, 2015
When the amount of labeled data are limited, semisupervised learning can improve the learner's performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the un...
Datasets as Topic Pattern Recognition, Automated Support Vector Machine Supervised Machine Learning
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Robust supervised segmentation of neuropathology whole-slide microscopy images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jan 1, 2015
Alzheimer's disease is characterized by brain pathological aggregates such as Aβ plaques and neurofibrillary tangles which trigger neuroinflammation and participate to neuronal loss. Quantification of these pathological markers on histological sectio...
Image Processing, Computer-Assisted Supervised Machine Learning Signal-To-Noise Ratio Humans Mice Alzheimer Disease Brain Neurofibrillary Tangles Color Microscopy Animals Plaque, Amyloid
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Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jan 1, 2015
Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine le...
Sensitivity and Specificity Image Interpretation, Computer-Assisted Longitudinal Studies Humans Radiography Supervised Machine Learning Brain Aged Alzheimer Disease Positron-Emission Tomography
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Force-feedback sensory substitution using supervised recurrent learning for robotic-assisted surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jan 1, 2015
The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach th...
Humans Feedback Robotic Surgical Procedures Neural Networks, Computer Supervised Machine Learning
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Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.

Bio-medical materials and engineering Jan 1, 2015
The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these ch...
Computer Simulation Female Reproducibility of Results Sensitivity and Specificity Stochastic Processes Breast Neoplasms Humans Radiographic Image Enhancement Models, Statistical Neural Networks, Computer Algorithms Supervised Machine Learning Sample Size Pattern Recognition, Automated Data Interpretation, Statistical False Positive Reactions Radiographic Image Interpretation, Computer-Assisted
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Automated Detection of Health Websites' HONcode Conformity: Can N-gram Tokenization Replace Stemming?

Studies in health technology and informatics Jan 1, 2015
Authors evaluated supervised automatic classification algorithms for determination of health related web-page compliance with individual HONcode criteria of conduct using varying length character n-gram vectors to represent healthcare web page docume...
Consumer Health Information Guideline Adherence Feasibility Studies Practice Guidelines as Topic Supervised Machine Learning Internationality Natural Language Processing Pattern Recognition, Automated Internet
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Automated Detection of Postoperative Surgical Site Infections Using Supervised Methods with Electronic Health Record Data.

Studies in health technology and informatics Jan 1, 2015
The National Surgical Quality Improvement Project (NSQIP) is widely recognized as "the best in the nation" surgical quality improvement resource in the United States. In particular, it rigorously defines postoperative morbidity outcomes, including su...
Surgical Wound Infection Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Decision Support Systems, Clinical Supervised Machine Learning Data Mining Humans Electronic Health Records
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