OBJECTIVE: In the automatic lung nodule detection system, the authenticity of a large number of nodule candidates needs to be judged, which is a classification task. However, the variable shapes and sizes of the lung nodules have posed a great challe...
BMC medical informatics and decision making
Nov 6, 2019
BACKGROUND: For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While there have been many studies...
White blood cells (WBC) are important parts of our immune system and they protect our body against infections by eliminating viruses, bacteria, parasites and fungi. There are five types of WBC. These are called Lymphocytes, Monocytes, Eosinophils, Ba...
There have been several empirical studies addressing breast cancer using machine learning and soft computing techniques. Many claim that their algorithms are faster, easier, or more accurate than others are. This study is based on genetic programming...
PURPOSE: To develop and compare the predictive performance of machine-learning algorithms to estimate the risk of quality-adjusted life year (QALY) lower than or equal to 30 days (30-day QALY).
PURPOSE: The aim of this study was to develop an interactive deep learning-assisted identification of the hyperdense middle cerebral artery (MCA) sign (HMCAS) on non-contrast computed tomography (CT) among patients with acute ischemic stroke.
The neuromuscular disorders are diagnosed using electromyographic (EMG) signals. Machine learning algorithms are employed as a decision support system to diagnose neuromuscular disorders. This paper compares bagging and boosting ensemble learning met...
Urothelial carcinoma of the bladder (UCB) is the most common urinary cancer. White-light cystoscopy (WLC) forms the corner stone for the diagnosis of UCB. However, histopathological assessment is required for adjuvant treatment selection. Probe-base...
The present study developed a feature selection (FS)-based decision support system using the electroencephalography (EEG) signals recorded from neonates with and without seizures. The study employed 10 different FS algorithms to reduce the classifica...
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