Published in BMC Bioinformatics
BackgroundIn recent years, the rapid development of single-cell RNA-sequencing (scRNA-seq) techniques enables the quantitative characterization of cell types at a single-cell resolution. With the explosive growth of the number of cells profiled in individual scRNA-seq experiments, there is a demand for novel computational methods for classifying ne...
Published in BMC Bioinformatics
BackgroundThe development of Next Generation Sequencing (NGS) has had a major impact on the study of genetic sequences. Among problems that researchers in the field have to face, one of the most challenging is the taxonomic classification of metagenomic reads, i.e., identifying the microorganisms that are present in a sample collected directly from...
Published in Machine Vision and Applications
Chromosome analysis is an important approach to detecting genetic diseases. However, the process of identifying chromosomes in metaphase images can be challenging and time-consuming. Therefore, it is important to use automatic methods for detecting chromosomes to aid diagnosis. This work proposes a study of deep learning approaches for classificati...
Published in Human-centric Computing and Information Sciences
The fast propagation of the Internet of Things (IoT) devices has driven to the development of collaborative healthcare frameworks to support the next generation healthcare industry for quality medical healthcare. This paper presents a generalized collaborative framework named collaborative shared healthcare plan (CSHCP) for cognitive health and fit...
Published in Social Network Analysis and Mining
Social media has evolved itself as a significant tool used by people for information spread during emergencies like natural or man-made disasters. Real-time analysis of this huge collected data can play a vital role in crisis estimation, response and assistance exercises. We propose a novel prototype system that analyzes the emergency-related tweet...
Published in Diabetologia
Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and...
Published in The journal of spinal cord medicine
Context/Objective: The sacral examination components of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), namely deep anal pressure (DAP) and voluntary anal sphincter contraction (VAC), are often difficult to perform. We evaluated whether pressure sensation at the S3 dermatome (S3P), and voluntary hip addu...
Published in Diagnostic and interventional imaging
The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches. A total of 147 patients were included in this retrospective single-center study. There were 12 men and 135 women with a mean age of 56.88±10.6 (SD) years (range: 28-87 years). For each ...
Visually impaired people cannot use classical maps but can learn to use tactile relief maps. These tactile maps are crucial at school to learn geography and history as well as the other students. They are produced manually by professional transcriptors in a very long and costly process. A platform able to generate tactile maps from maps scanned fro...
Published in Burns : journal of the International Society for Burn Injuries
Accurate classification of burn severities is of vital importance for proper burn treatments. A recent article reported that using the combination of Raman spectroscopy and optical coherence tomography (OCT) classifies different degrees of burns with an overall accuracy of 85% [1]. In this study, we demonstrate the feasibility of using Raman spectr...
