OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; t...
A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients. Several kidney graft outcome prediction models, developed using machine learning methods, are...
Discovering technology opportunities from the opinion of users can promote successful technological development by satisfying the needs of users. However, although previous approaches using opinion mining only have classified various needs of users i...
IEEE journal of biomedical and health informatics
Oct 28, 2019
Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of liver cancer and is routinely performed manually. However, this pro...
BACKGROUND: Minimally invasive single-port surgery is often associated with large incisions up to 2-3 cm, complicated handling due to the lack of triangulation, and instrument crossing. Aim of this prospective study was to perform true single-port su...
Lung cancer is the leading cause of cancer death worldwide. Early detection of lung cancer is helpful to provide the best possible clinical treatment for patients. Due to the limited number of radiologist and the huge number of chest x-ray radiograph...
Artificial intelligence is a growing phenomenon that is driving major changes to how we deliver healthcare. One of its most significant and challenging contributions is likely to be in diagnosis. Artificial intelligence is challenging the physician's...
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...
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Oct 28, 2019
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsin...
Forensic science international. Genetics
Oct 28, 2019
We present a machine learning approach to short tandem repeat (STR) sequence detection and extraction from massively parallel sequencing data called Fragsifier. Using this approach, STRs are detected on each read by first locating the longest repeat ...
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