AIMC Topic: False Positive Reactions

Clear Filters Showing 121 to 130 of 157 articles

Machine Learning Approach to Automated Quality Identification of Human Induced Pluripotent Stem Cell Colony Images.

Computational and mathematical methods in medicine Jul 14, 2016
The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient's cells are reprogrammed back to stem cells and ar...
Regenerative Medicine Pattern Recognition, Automated False Positive Reactions Cell Culture Techniques Bayes Theorem Least-Squares Analysis Quality Control Induced Pluripotent Stem Cells Humans Machine Learning Algorithms Reproducibility of Results Support Vector Machine Fibroblasts Models, Statistical
View on PubMed DOI

A Fuzzy Permutation Method for False Discovery Rate Control.

Scientific reports Jun 22, 2016
Biomedical researchers often encounter the large-p-small-n situations-a great number of variables are measured/recorded for only a few subjects. The authors propose a fuzzy permutation method to address the multiple testing problem for small sample s...
Models, Statistical Sample Size False Positive Reactions Monte Carlo Method Biomedical Research Fuzzy Logic
View on PubMed DOI

Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.

PloS one May 19, 2016
This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious ...
Databases, Factual Electronic Health Records Models, Theoretical Support Vector Machine Humans Software Algorithms Medical Informatics Regression Analysis False Positive Reactions Benchmarking Health Services Research Data Mining
View on PubMed DOI

Liver vessel segmentation based on extreme learning machine.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) May 4, 2016
Liver-vessel segmentation plays an important role in vessel structure analysis for liver surgical planning. This paper presents a liver-vessel segmentation method based on extreme learning machine (ELM). Firstly, an anisotropic filter is used to remo...
Liver Diffusion Radiotherapy Planning, Computer-Assisted False Positive Reactions Sensitivity and Specificity Imaging, Three-Dimensional Image Processing, Computer-Assisted Radiography, Abdominal Humans Anisotropy Machine Learning Algorithms Tomography, X-Ray Computed Reproducibility of Results
View on PubMed DOI

Detecting false positive sequence homology: a machine learning approach.

BMC bioinformatics Feb 24, 2016
BACKGROUND: Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to ...
False Positive Reactions Machine Learning Sequence Alignment Sequence Homology
View on PubMed DOI

Computer-Aided Diagnosis of Parkinson's Disease Using Enhanced Probabilistic Neural Network.

Journal of medical systems Sep 29, 2015
Early and accurate diagnosis of Parkinson's disease (PD) remains challenging. Neuropathological studies using brain bank specimens have estimated that a large percentages of clinical diagnoses of PD may be incorrect especially in the early stages. In...
Parkinson Disease Diagnosis, Differential Algorithms False Positive Reactions Diagnosis, Computer-Assisted Humans Physical Examination ROC Curve Neural Networks, Computer Support Vector Machine
View on PubMed DOI

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 23, 2015
Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal ...
Evoked Potentials, Somatosensory Humans Spinal Cord False Positive Reactions Artificial Intelligence Intraoperative Neurophysiological Monitoring Spinal Cord Injuries Algorithms Support Vector Machine Decision Making, Computer-Assisted Computer Systems Least-Squares Analysis
View on PubMed DOI

Sample Selection for Training Cascade Detectors.

PloS one Jul 21, 2015
Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represe...
Computational Biology Mammography Area Under Curve Radiographic Image Interpretation, Computer-Assisted Pedestrians Humans Databases, Factual Female Pattern Recognition, Automated Artificial Intelligence Breast Neoplasms False Positive Reactions Algorithms ROC Curve Facial Recognition
View on PubMed DOI

A novel method based on physicochemical properties of amino acids and one class classification algorithm for disease gene identification.

Journal of biomedical informatics Jul 2, 2015
Identifying the genes that cause disease is one of the most challenging issues to establish the diagnosis and treatment quickly. Several interesting methods have been introduced for disease gene identification for a decade. In general, the main diffe...
Support Vector Machine Parkinson Disease Regression Analysis Proteins Principal Component Analysis Amino Acids Amino Acid Sequence Probability Reproducibility of Results Diagnosis, Computer-Assisted ROC Curve Computational Biology Humans Artificial Intelligence Algorithms False Positive Reactions
View on PubMed DOI

Revisiting Warfarin Dosing Using Machine Learning Techniques.

Computational and mathematical methods in medicine Jun 4, 2015
Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographi...
Databases, Factual Anticoagulants Female Humans Pharmacogenetics Reproducibility of Results Machine Learning Warfarin Genotype Algorithms Male Drug Administration Schedule Dose-Response Relationship, Drug False Positive Reactions Regression Analysis
View on PubMed DOI
Popular Topics
Recent Journals