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Lightme: analysing language in internet support groups for mental health
ConclusionIt is possible to build a competitive triage classifier using features derivedonly from the textual content of the post. Further research needs to be done in order to translate our quantitative and qualitative findings into features, as it may improve overall performance. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 13, 2020 Category: Information Technology Source Type: research

Automated epilepsy detection techniques from electroencephalogram signals: a review study
AbstractEpilepsy is a serious neurological condition which contemplates as top 5 reasons for avoidable mortality from ages 5 –29 in the worldwide. The avoidable deaths due to epilepsy can be reduced by developing efficient automated epilepsy detection or prediction machines or software. To develop an automated epilepsy detection framework, it is essential to properly understand the existing techniques and their benefit as well as detriment also. This paper aims to provide insight on the information about the existing epilepsy detection and classification techniques as they are crucial for supporting clinical-decision in ...
Source: Health Information Science and Systems - October 12, 2020 Category: Information Technology Source Type: research

Automated detection of mild and multi-class diabetic eye diseases using deep learning
AbstractDiabetic eye disease is a collection of ocular problems that affect patients with diabetes. Thus, timely screening enhances the chances of timely treatment and prevents permanent vision impairment. Retinal fundus images are a useful resource to diagnose retinal complications for ophthalmologists. However, manual detection can be laborious and time-consuming. Therefore, developing an automated diagnose system reduces the time and workload for ophthalmologists. Recently, the image classification using Deep Learning (DL) in between healthy or diseased retinal fundus image classification already achieved a state of the...
Source: Health Information Science and Systems - October 8, 2020 Category: Information Technology Source Type: research

Improving accessibility of the Australian My Health Records while preserving privacy and security of the system
AbstractAustralian My Health Record (MyHR) is a significant development in empowering patients, allowing them to access their summarised health information themselves and to share the information with all health care providers involved in their care. Consequently, the MyHR system must enable efficient availability of meaningful, accurate, and complete data to assist an improved clinical administration of a patient. However, while enabling this, protecting data privacy and ensuring security in the MyHR system has become a major concern because of its consequences in promoting high standards of patient care. In this paper, w...
Source: Health Information Science and Systems - October 8, 2020 Category: Information Technology Source Type: research

Analysis of the global situation of COVID-19 research based on bibliometrics
We described and analyzed current COVID-19 research from the perspectives of international cooperation, interdisciplinary cooperation, and research hotspots using a bibliometric clustering algorithm. Using the diagnosis and treatment guidelines of the WHO and the United States and China as examples, we evaluate the transformation of scientific results from basic research to applications. Scientific research results that have not yet been incorporated into these guidelines are summarized to encourage updates and improvements by applying scientific research to prevention and control. COVID-19 has fostered interdisciplinary c...
Source: Health Information Science and Systems - September 29, 2020 Category: Information Technology Source Type: research

The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection
AbstractCOVID-19 is a novel virus, which has a fast spreading rate, and now it is seen all around the world. The case and death numbers are increasing day by day. Some tests have been used to determine the COVID-19. Chest X-ray and chest computerized tomography (CT) are two important imaging tools for determination and monitoring of COVID-19. And new methods have been searching for determination of the COVID-19. In this paper, the investigation of various multiresolution approaches in detection of COVID-19 is carried out. Chest X-ray images are used as input to the proposed approach. As recent trend in machine learning shi...
Source: Health Information Science and Systems - September 28, 2020 Category: Information Technology Source Type: research

Estimation of infection density and epidemic size of COVID-19 using the back-calculation algorithm
AbstractThe novel coronavirus (COVID-19) is continuing its spread across the world, claiming more than 160,000 lives and sickening more than 2,400,000 people as of April 21, 2020. Early research has reported a basic reproduction number (R0) between 2.2 to 3.6, implying that the majority of the population is at risk of infection if no intervention measures were undertaken. The true size of the COVID-19 epidemic remains unknown, as a significant proportion of infected individuals only exhibit mild symptoms or are even asymptomatic. A timely assessment of the evolving epidemic size is crucial for resource allocation and triag...
Source: Health Information Science and Systems - September 27, 2020 Category: Information Technology Source Type: research

PDCOVIDNet: a parallel-dilated convolutional neural network architecture for detecting COVID-19 from chest X-ray images
AbstractThe COVID-19 pandemic continues to severely undermine the prosperity of the global health system. To combat this pandemic, effective screening techniques for infected patients are indispensable. There is no doubt that the use of chest X-ray images for radiological assessment is one of the essential screening techniques. Some of the early studies revealed that the patient ’s chest X-ray images showed abnormalities, which is natural for patients infected with COVID-19. In this paper, we proposed a parallel-dilated convolutional neural network (CNN) based COVID-19 detection system from chest X-ray images, named as P...
Source: Health Information Science and Systems - September 20, 2020 Category: Information Technology Source Type: research

Variability analysis of epileptic EEG using the maximal overlap discrete wavelet transform
ConclusionThe use of the MODWT in examining the variances and changes in variance did not show specific patterns which differentiate between seizure and non-seizure channels. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - September 14, 2020 Category: Information Technology Source Type: research

A semantic trajectory data warehouse for improving nursing productivity
The objective is the observation, management and scheduling of nurses’ shifts data by the computation of OLAP operations over them. A prototype implementation has also be en realized to illustrate the functionality of the proposed model. The produced results prove the efficiency in improving nursing productivity. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - August 28, 2020 Category: Information Technology Source Type: research

The correlation of everyday cognition test scores and the progression of Alzheimer ’s disease: a data analytics study
In this study, we investigate two versions of the ECog test: the study partner reported version (ECogSP), and the patient reported version (ECogPT). We compare these, using statistical analysis and machine learning techniques, to create classification models to demonstrate the progression in ECog scores over time by using the Alzheimer’s Disease Neuroimaging Initiative longitudinal data repository (ADNI); participants are classed with having normal cognition, mild cognitive impairment, or Alzheimer’s disease. We found that participants who are diagnosed with Alzheimer’s disease at baseline, or during a subsequent vis...
Source: Health Information Science and Systems - July 22, 2020 Category: Information Technology Source Type: research

An embedded novel compact feature profile image in speech signal for teledermoscopy system
ConclusionThis work established that the newly proposed CFP watermarked in speech signal using the DWT-based modified SVD followed by single-level decomposition Db1 with hard thresholding wavelet denoising achieved efficient diagnostic teledermoscopy system. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 24, 2020 Category: Information Technology Source Type: research

RSMOTE: improving classification performance over imbalanced medical datasets
ConclusionBased on the minority sample density analysis, we propose RSMOTE method that divides the minority sample domain into four regions. The proposed RSMOTE includes four re-sampling methods that each of them carries out resampling on a specific region. According to the experimental results, resampling on the regions with high minority sample density obtained better results while those with lower minority sample density got the inferior results. Thus, we conclude that the RSMOTE is a more flexible resampling method for the imbalanced medical datasets that is capable of generating samples with various minority sample de...
Source: Health Information Science and Systems - June 11, 2020 Category: Information Technology Source Type: research

Synthesis of fracture radiographs with deep neural networks
ConclusionOur method generates X-rays realistic enough to be indistinguishable from real X-rays. We also show that synthetic images generated using this method can be used to increase the accuracy of deep classifiers on clinically meaningful subsets of fracture X-rays. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - May 29, 2020 Category: Information Technology Source Type: research

Local feature descriptors based ECG beat classification
In this study, we propose a different approach for ECG beat classification. The proposed approach is based on image processing. Thus, the initial step of the proposed work is converting the ECG beat signals to the ECG beat images. To do that, the ECG beat snapshots are initially saved as ECG beat images and then local feature descriptors are considered for feature extraction from ECG beat images. Eight local feature descriptors namely Local Binary Patterns, Frequency Decoded LBP, Quaternionic Local Ranking Binary Pattern, Binary Gabor Pattern, Local Phase Quantization, Binarized Statistical Image Features, CENsus TRansform...
Source: Health Information Science and Systems - May 1, 2020 Category: Information Technology Source Type: research