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False Positive Reactions

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Reducing false arrhythmia alarm rates using robust heart rate estimation and cost-sensitive support vector machines.

Physiological measurement
To lessen the rate of false critical arrhythmia alarms, we used robust heart rate estimation and cost-sensitive support vector machines. The PhysioNet MIMIC II database and the 2015 PhysioNet/CinC Challenge public database were used as the training d...

A ℓ norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

Computer methods and programs in biomedicine
OBJECTIVE: The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD).

Lung nodule classification using deep feature fusion in chest radiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lung nodules are small, round, or oval-shaped masses of tissue in the lung region. Early diagnosis and treatment of lung nodules can significantly improve the quality of patients' lives. Because of their small size and the interlaced nature of chest ...

Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in lung cancer diagnosis and early treatment. The objective of this paper is to effectively add...

Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering ...

Reducing false alarms in the ICU by quantifying self-similarity of multimodal biosignals.

Physiological measurement
False arrhythmia alarms pose a major threat to the quality of care in today's ICU. Thus, the PhysioNet/Computing in Cardiology Challenge 2015 aimed at reducing false alarms by exploiting multimodal cardiac signals recorded by a patient monitor. False...

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...