AIMC Topic: False Positive Reactions

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Reduction of false arrhythmia alarms using signal selection and machine learning.

Physiological measurement
In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm is true or false. The large number of false alarms in intensive care is a severe issue. The noise peaks caused by alarms can be high and in a noisy en...

Suppression of false arrhythmia alarms in the ICU: a machine learning approach.

Physiological measurement
This paper presents a novel approach for false alarm suppression using machine learning tools. It proposes a multi-modal detection algorithm to find the true beats using the information from all the available waveforms. This method uses a variety of ...

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

Computational and mathematical methods in medicine
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...

A Fuzzy Permutation Method for False Discovery Rate Control.

Scientific reports
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...

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

PloS one
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 ...

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)
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...

Detecting false positive sequence homology: a machine learning approach.

BMC bioinformatics
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 ...

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

Journal of medical systems
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...

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
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 ...

Sample Selection for Training Cascade Detectors.

PloS one
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...