A stacked LSTM for atrial fibrillation prediction based on multivariate ECGs
AbstractAtrial fibrillation (AF) is an irregular and rapid heart rate that can increase the risk of various heart-related complications, such as the stroke and the heart failure. Electrocardiography (ECG) is widely used to monitor the health of heart disease patients. It can dramatically improve the health and the survival rate of heart disease patients by accurately predicting the AFs in an ECG. Most of the existing researches focus on the AF detection, but few of them explore the AF prediction. In this paper, we develop a recurrent neural network (RNN) composed of stacked LSTMs for AF prediction, which called SLAP. This ...
Source: Health Information Science and Systems - April 21, 2020 Category: Information Technology Source Type: research

Keyword extraction and structuralization of medical reports
AbstractPurposeIn recent years, patients usually accept more accurate and detailed examinations because of the rapid advances in medical technology. Many of the examination reports are not represented in numerical data, but text documents written by the medical examiners based on the observations from the instruments and biochemical tests. If the above-mentioned unstructured data can be organized as a report in a structured form, it will help doctors to understand a patient's status of the various examinations more efficiently. Besides, further association analysis on the structuralized data can be performed to identify po...
Source: Health Information Science and Systems - April 3, 2020 Category: Information Technology Source Type: research

A decision support system for mammography reports interpretation
ConclusionsAccordingly, data mining approaches are proved to be a helpful tool to make the final decision as to whether patients should be referred to biopsy or not based on mammography reports. The developed CDSS may also be helpful especially for less experienced radiologists. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - April 1, 2020 Category: Information Technology Source Type: research

Cardiotocograph-based labor stage classification from uterine contraction pressure during ante-partum and intra-partum period: a fuzzy theoretic approach
AbstractComputerized techniques for Cardiotocograph (CTG) based labor stage classification would support obstetrician for advance CTG analysis and would improve their predictive power for fetal heart rate (FHR) monitoring. Intrapartum fetal monitoring is necessary as it can detect the event, which ultimately leads to hypoxic ischemic encephalopathy, cerebral palsy or even fetal demise. To bridge this gap, in this paper, we propose an automated decision support system that will help the obstetrician identify the status of the fetus during ante-partum and intra-partum period. The proposed algorithm takes 30  min of 275 ...
Source: Health Information Science and Systems - March 30, 2020 Category: Information Technology Source Type: research

A space-frequency localized approach of spatial filtering for motor imagery classification
AbstractClassification of Motor Imagery (MI) signals is the heart of Brain-Computer Interface (BCI) based applications. Spatial filtering is an important step in this process that produce new set of signals for better discrimination of two classes of EEG signals. In this work, a new approach of spatial filtering called Space-Frequency Localized Spatial Filtering (SFLSF) is proposed to enhance the performances of MI classification. The SFLSF method initially divides the scalp-EEG channels into local overlapping spatial windows. Then a filter bank is used to divide the signals into local frequency bands. The group of channel...
Source: Health Information Science and Systems - March 28, 2020 Category: Information Technology Source Type: research

Predicting risk of stillbirth and preterm pregnancies with machine learning
In this study, we utilize state-of-the-art machine learning methods in the task of predicting early stillbirth, late stillbirth and preterm birth pregnancies. The aim of this experimentation is to discover novel risk models that could be utilized in a clinical setting. A CDC data set of almost sixteen million observations was used conduct feature selection, parameter optimization and verification of proposed models. An additional NYC data set was used for external validation. Algorithms such as logistic regression, artificial neural network and gradient boosting decision tree were used to construct individual classifiers. ...
Source: Health Information Science and Systems - March 25, 2020 Category: Information Technology Source Type: research

Bio-inspired dimensionality reduction for Parkinson ’s disease (PD) classification
AbstractGiven the demand for developing the efficient Machine Learning (ML) classification models for healthcare data, and the potentiality of Bio-Inspired Optimization (BIO) algorithms to tackle the problem of high dimensional data, we investigate the range of ML classification models trained with the optimal subset of features of PD data set for efficient PD classification. We used two BIO algorithms, Genetic Algorithm (GA) and Binary Particle Swarm Optimization (BPSO), to determine the optimal subset of features of PD data set. The data set chosen for investigation comprises 756 observations (rows or records) taken over...
Source: Health Information Science and Systems - March 9, 2020 Category: Information Technology Source Type: research

Automatic approach for constructing a knowledge graph of knee osteoarthritis in Chinese
In this study, a medical knowledge graph is constructed from the electronic medical record text of knee osteoarthritis patients to support intelligent medical applications such as knowledge retrieval and decision support, and to promote the sharing of medical resources. After constructing the domain ontology of knee osteoarthritis and manually labeling, we trained a machine learning model to automatically perform entity recognition and entity relation extraction, and then used a graph database to construct the knowledge graph of knee osteoarthritis. The experiment proves that the knowledge graph is comprehensive and reliab...
Source: Health Information Science and Systems - February 27, 2020 Category: Information Technology Source Type: research

Nutrient analysis of school lunches and anthropometric measures in a private and public school in Chennai, India
This study served to assess the impact of the School Lunch Program in India and observe measures related to nutrition adequacy and stunting in school aged children in Chennai, India. Dietary and anthropometric data were collected among students of ages 7 to 10 in a privately funded (n = 64) and a publicly funded school (n = 28). Bioelectrical Impedance Analysis was assessed for private school students. BMI for Age Z-scores for the private school (0.05 ± 1.36) (mean ± standard deviation) and public school (− 0.91 ± 2.01) ...
Source: Health Information Science and Systems - February 27, 2020 Category: Information Technology Source Type: research

Constructing a knowledge-based heterogeneous information graph for medical health status classification
This study has also contributed a model to medical practice to help practitioners become more confident in making final decisions in diagnosing illness. Moreover, this study affi rmed that biomedical literature could assist in building a classification model. This contribution will be advantageous for future researchers in mining the knowledge-base to develop different kinds of classification models. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - February 14, 2020 Category: Information Technology Source Type: research

A study of factors related to patients ’ length of stay using data mining techniques in a general hospital in southern Iran
ConclusionThe results showed that most of the proposed models are suitable for classification of the length of stay, although the Logistic Regression might have a slightly better performance than others in term of accuracy, and this model can be used to determine the patients ’ Length of Stay. In general, continuous monitoring of the factors influencing each of the performance indicators based on proper and accurate models in hospitals is important for helping management decisions. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - February 1, 2020 Category: Information Technology Source Type: research

Predicting healthcare professionals ’ intention to use poison information system in a Malaysian public hospital
ConclusionThe results of this study provided useful insights for healthcare agencies to understand the underlying elements that could improve the poison information management. The results proved that attitude and computer anxiety were critical factors among healthcare professionals managing poisoning cases in a highly stressful and unpredictable work environment. These factors must, therefore, be considered before implementing PIS in managing poisoning cases. The study also provided an understanding of how to improve system development by utilising the end user ’s expectation on the implementation of the system. (So...
Source: Health Information Science and Systems - January 3, 2020 Category: Information Technology Source Type: research

Dental caries diagnosis in digital radiographs using back-propagation neural network
ConclusionsThis study suggests that dental caries can be predicted more accurately with back-propagation neural network. There is a need for improving the system for classification of caries depth. More improved algorithms and high quantity and high quality datasets may give still better tooth decay detection in clinical dental practice. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - January 3, 2020 Category: Information Technology Source Type: research

Classification and prediction of diabetes disease using machine learning paradigm
ConclusionThe combination of LR and RF-based classifier performs better. This combination will be very helpful for predicting diabetic patients. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - January 3, 2020 Category: Information Technology Source Type: research

Outcome measures used in the smartphone applications for the management of low back pain: a systematic scoping review
ConclusionThe overall quality of the SPApps for LBP is low. Only very few SPApps offer outcome measures to monitor their effectiveness in the management of LBP. There is very limited evidence to show that the outcome measures used in the apps represents all the four core sets of LBP criteria set by ICF. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - January 2, 2020 Category: Information Technology Source Type: research

An efficient approach for physical actions classification using surface EMG signals
AbstractPhysical actions classification of surface electromyography (sEMG) signal is required in applications like prosthesis, and robotic control etc. In this paper, tunable-Q factor wavelet transform (TQWT) based algorithm is proposed for the classification of physical actions such as clapping, hugging, bowing, handshaking, standing, running, jumping, waving, seating, and walking. sEMG signal is decomposed into sub-bands by TQWT. Various features are extracted from each different band and statistical analysis is performed. These features are fed into multi-class least squares support vector machine classifier using two n...
Source: Health Information Science and Systems - December 23, 2019 Category: Information Technology Source Type: research

Convolutional neural networks based efficient approach for classification of lung diseases
AbstractTreatment of lung diseases, which are the third most common cause of death in the world, is of great importance in the medical field. Many studies using lung sounds recorded with stethoscope have been conducted in the literature in order to diagnose the lung diseases with artificial intelligence-compatible devices and to assist the experts in their diagnosis. In this paper, ICBHI 2017 database which includes different sample frequencies, noise and background sounds was used for the classification of lung sounds. The lung sound signals were initially converted to spectrogram images by using time –frequency met...
Source: Health Information Science and Systems - December 23, 2019 Category: Information Technology Source Type: research

A novel weighted compressive sensing using L1-magic recovery technique in medical image compression
AbstractRecent technological advancement in computing technology, communication systems, and machine learning techniques provides opportunities to biomedical engineers to achieve the requirements of clinical practice. This requires storage and/or transmission of medical images with the conservation of the medical information over the communication channel. Accordingly, medical compression is necessary for efficient channel bandwidth utilization. To solve the trade-off between the compression ratio and the preservation of significant information, compressed sensing (CS) can be used. During image recovery in CS, an optimizat...
Source: Health Information Science and Systems - December 23, 2019 Category: Information Technology Source Type: research

Guest Editorial: Special issue on “Application of artificial intelligence in health research”
(Source: Health Information Science and Systems)
Source: Health Information Science and Systems - December 6, 2019 Category: Information Technology Source Type: research

Artery/vein classification of retinal vessels using classifiers fusion
AbstractThe morphological changes in retinal blood vessels indicate cardiovascular diseases and consequently those diseases lead to ocular complications such as Hypertensive Retinopathy. One of the significant clinical findings related to this ocular abnormality is alteration of width of vessel. The classification of retinal vessels into arteries and veins in eye fundus images is a relevant task for the automatic assessment of vascular changes. This paper presents an important approach to solve this problem by means of feature ranking strategies and multiple classifiers decision-combination scheme that is specifically adap...
Source: Health Information Science and Systems - November 8, 2019 Category: Information Technology Source Type: research

Document recommendation based on interests of co-authors for brain science
AbstractPersonalized knowledge recommendation is an effective measure to provide individual information services in the field of brain science. It is essential that a complete understanding of authors ’ interests and accurate recommendation are carried out to achieve this goal. In this paper, a collaborative recommendation method based on co-authorship is proposed to make. In our approach, analysis of collaborators’ interests and the calculation of collaborative value are used for recommendat ions. Finally, the experiments using real documents associated with brain science are given and provide supports for col...
Source: Health Information Science and Systems - November 4, 2019 Category: Information Technology Source Type: research

An E-health system for monitoring elderly health based on Internet of Things and Fog computing
AbstractWith the significant increase in the number of elderly in the world and the resulting health problems of these increasing, finding technical solutions to address this problem has become a pressing necessity, particularly in the field of health care. This paper proposes an e-health system for monitoring elderly health based on the Internet of Things (IoT) and Fog computing. The system was developed using Mysignals HW V2 platform and an Android app that plays the role of Fog server, which enables the collection of physiological parameters and general health parameters from elderly periodically. This Android app enabl...
Source: Health Information Science and Systems - October 24, 2019 Category: Information Technology Source Type: research

Colon cancer data analysis by chameleon algorithm
AbstractDetecting the key differential genes of colon cancers is very important to tell colon cancer patients from normal people. A gene selection algorithm for colon cancers is proposed by using the dynamic modeling properties of chameleon algorithm and its capability to discover any arbitrary shape clusters. This chameleon algorithm based gene selection algorithm comprises three steps. The first step is to select those genes with higher Fisher function values as candidate genes. The second step is to detect gene groups by using chameleon algorithm based on Euclidean distance. The third step is to select the most importan...
Source: Health Information Science and Systems - October 14, 2019 Category: Information Technology Source Type: research

Modeling and classification of voluntary and imagery movements for brain –computer interface from fNIR and EEG signals through convolutional neural network
AbstractPractical brain –computer interface (BCI) demands the learning-based adaptive model that can handle diverse problems. To implement a BCI, usually functional near-infrared spectroscopy (fNIR) is used for measuring functional changes in brain oxygenation and electroencephalography (EEG) for evaluating the neuronal electric potential regarding the psychophysiological activity. Since the fNIR modality has an issue of temporal resolution, fNIR alone is not enough to achieve satisfactory classification accuracy as multiple neural stimuli are produced by voluntary and imagery movements. This leads us to make a com b...
Source: Health Information Science and Systems - October 12, 2019 Category: Information Technology Source Type: research

Neural attention with character embeddings for hay fever detection from twitter
AbstractThe paper aims to leverage the highly unstructured user-generated content in the context of pollen allergy surveillance using neural networks with character embeddings and the attention mechanism. Currently, there is no accurate representation of hay fever prevalence, particularly in real-time scenarios. Social media serves as an alternative to extract knowledge about the condition, which is valuable for allergy sufferers, general practitioners, and policy makers. Despite tremendous potential offered, conventional natural language processing methods prove limited when exposed to the challenging nature of user-gener...
Source: Health Information Science and Systems - October 12, 2019 Category: Information Technology Source Type: research

Cognitive modelling of Chinese herbal medicine ’s effect on breast cancer
ConclusionFCMs can visually represent the cognitive knowledge, particularly the causal relationship among key factors of TCM effects and the related breast cancer status. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 3, 2019 Category: Information Technology Source Type: research

Imputation techniques on missing values in breast cancer treatment and fertility data
This study examines a series of machine learning based imputation methods and suggests an efficient approach to in preparing a good quality breast cancer (BC) dataset, to find the relationship between BC treatment and chemotherapy-related amenorrhoea, where the performance is evaluated with the accuracy of the prediction. To this end, the reliability and robustness of six well-known imputation methods are evaluated. Our results show that imputation leads to a significant boost in the classification performance compared to the model prediction based on listwise deletion. Furthermore, the results reveal that most methods gai...
Source: Health Information Science and Systems - October 3, 2019 Category: Information Technology Source Type: research

Multi-objective semi-supervised clustering to identify health service patterns for injured patients
ConclusionThe proposed multi-objective semi-supervised clustering finds the optimal clusters that not only are well-separated from each other but can provide informative insights regarding the outcome of interest. It also overcomes two drawback of clustering methods such as being sensitive to the initial cluster centers and need for specifying the number of clusters. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - August 29, 2019 Category: Information Technology Source Type: research

Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models
AbstractIntroductionCardiotocography (CTG) consists of two biophysical signals that are fetal heart rate (FHR) and uterine contraction (UC). In this research area, the computerized systems are usually utilized to provide more objective and repeatable results.Materials and MethodsFeature selection algorithms are of great importance regarding the computerized systems to not only reduce the dimension of feature set but also to reveal the most relevant features without losing too much information. In this paper, three filters and two wrappers feature selection methods and machine learning models, which are artificial neural ne...
Source: Health Information Science and Systems - August 20, 2019 Category: Information Technology Source Type: research

A performance based feature selection technique for subject independent MI based BCI
ConclusionThe conclusion of this study and its significance is that it developed a viable methodology for simple, efficient feature selection and BCI algorithm development, which leads to an overall increase in algorithm classification accuracy. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - August 7, 2019 Category: Information Technology Source Type: research

Towards the classification of heart sounds based on convolutional deep neural network
ConclusionsThe obtained results are compared with some of the existing methods. The comparisons show that the proposed method outperformed. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - August 7, 2019 Category: Information Technology Source Type: research

Automated AJCC (7th edition) staging of non-small cell lung cancer (NSCLC) using deep convolutional neural network (CNN) and recurrent neural network (RNN)
ConclusionThe proposed CNN-RNN model performed commendably during the study. Further studies may be carried out to refine the model and develop an improved auxiliary decision support system for oncologists and radiologists. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - July 30, 2019 Category: Information Technology Source Type: research

Medical image enhancement in F-shift transformation domain
AbstractImage enhancement technology plays an important role in the diagnosis and treatment of medical diseases. In this paper, we propose a method to automatically enhance medical images. The proposed method could be used to support clinical medical diagnosis, adjuvant therapy and curative effect diagnosis. This scheme uses contrast limited adaptive histogram equalization (CLAHE) method in F-shift transformation domain. Firstly, we adjust the overall brightness of the underexposed or overexposed image. Secondly, we perform CLAHE to enhance the low-frequency components obtained by one-level two-dimensional F-shift transfor...
Source: Health Information Science and Systems - July 24, 2019 Category: Information Technology Source Type: research

A machine learning autism classification based on logistic regression analysis
AbstractAutistic Spectrum Disorder (ASD) is a neurodevelopmental condition associated with significant healthcare costs; early diagnosis could substantially reduce these. The economic impact of autism reveals an urgent need for the development of easily implemented and effective screening methods. Therefore, time-efficient ASD screening is imperative to help health professionals and to inform individuals whether they should pursue formal clinical diagnosis. Presently, very limited autism datasets associated with screening are available and most of them are genetic in nature. We propose new machine learning framework relate...
Source: Health Information Science and Systems - June 1, 2019 Category: Information Technology Source Type: research

Extracting features with medical sentiment lexicon and position encoding for drug reviews
AbstractMedical sentiment analysis refers to the extraction of sentiments or emotions from documents retrieved from healthcare sources, such as public forums and drug review websites. Previous studies prove that sentiment analysis for clinical documents has the potential for assisting patients with information for self assessing treatments, providing health professionals with more insights into patients ’ health conditions, or even managing relations between patients and doctors. Nevertheless, the lack of data used for empirical experiments in previous research indicates that there are strong needs for a systematic f...
Source: Health Information Science and Systems - May 30, 2019 Category: Information Technology Source Type: research

Ballistocardiogram signal processing: a review
AbstractAcross the world, healthcare costs are projected to continue to increase, and the pressure on the healthcare system is only going to grow in intensity as the rate of growth of elderly population increases in the coming decades. As an example, when people age one possible condition that they may experience is sleep-disordered breathing (SDB). SDB, better known as the obstructive sleep apnea (OSA) syndrome, and associated cardiovascular complications are among the most common clinical disorders. The gold-standard approach to accurately diagnose OSA, is polysomnography (PSG), a test that should be performed in a speci...
Source: Health Information Science and Systems - May 16, 2019 Category: Information Technology Source Type: research

Multi-level medical periodic patterns from human movement behaviors
AbstractHuman movement behaviors could reveal many interesting medical patterns. Due to the advances in location-aware devices, a large volume of human movement behaviors has been captured in the form of spatio-temporal trajectories. These spatio-temporal trajectories are useful resources for medical data mining, and they could be used to classify which trajectory passes through medical centres and which one does not. Traditional approaches utilise time-series datasets while ignoring spatio-temporal semantics in order to detect periodic patterns in medical domains. They also fail to consider the inherent hierarchical natur...
Source: Health Information Science and Systems - April 19, 2019 Category: Information Technology Source Type: research

Wavelet based deep learning approach for epilepsy detection
AbstractElectroencephalogram (EEG) signal contains vital details regarding electrical actions performed by the brain. Analysis of these signals is important for epilepsy detection. However, analysis of these signals can be tricky in nature and requires human expertise. The human factor can result in subjective and possible erroneous epilepsy detection. To tackle this problem, Machine Learning (ML) algorithms were introduced, to remove the human factor. However, this approach is counterintuitive in nature as it involves using complex features for epilepsy detection. Hence to tackle this problem we have introduced a wavelet ...
Source: Health Information Science and Systems - April 8, 2019 Category: Information Technology Source Type: research

Students university healthy lifestyle practice: quantitative analysis
AbstractThe development of human being passes through several transition phases throughout the life span. The most critical phase that may influence the individuals ’ lifestyle is the college admission. During this phase, the students are independent and they are responsible for their own lives especially if they are far away from parental home. A healthy lifestyle is identified by regular exercises, healthy diet, and organized sleeping pattern. However, the transfer into a new environment may alternate the usual habits and cause major fluctuations in lifestyle. The students may be vulnerable to several stressful fac...
Source: Health Information Science and Systems - March 19, 2019 Category: Information Technology Source Type: research

Words prediction based on N-gram model for free-text entry in electronic health records
In this study, by applying the trigram language model, we presented a method to predict the next words while typing free texts. It is hypothesized that using this system may save typing time of free text. The words prediction model introduced in this research was trained and tested on the free texts regarding to colonoscopy, transesophageal echocardiogram, and anterior-cervical-decompression. Required time of typing for each of the above-mentioned reports calculated and compared with manual typing of the same words. It is revealed that 33.36% reduction in typing time and 73.53% reduction in keystroke. The designed system r...
Source: Health Information Science and Systems - February 28, 2019 Category: Information Technology Source Type: research

Managing uncertainty in imputing missing symptom value for healthcare of rural India
ConclusionsIt is worth to mention that the system is for primary healthcare and in emergency cases, patients are referred to the experts. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - February 18, 2019 Category: Information Technology Source Type: research

“Similar query was answered earlier”: processing of patient authored text for retrieving relevant contents from health discussion forum
AbstractOnline remedy finders and health-related discussion forums have become increasingly popular in recent years. Common web users write their health problems there and request suggestion from experts or other users. As a result, these forums became a huge repository of information and discussions on various health issues. An intelligent information retrieval system can help to utilize this repository in various applications. In this paper, we propose a system for the automatic identification of existing similar forum posts given a new post. The system is based on computing similarity between two patient authored texts....
Source: Health Information Science and Systems - February 18, 2019 Category: Information Technology Source Type: research

Estimation of number of ever born children using zero truncated count model: evidence from Bangladesh Demographic and Health Survey
This study proposes zero truncated Poisson and zero truncated negative binomial regression models in order to find the best fitted model to estimate number of ever born children using BDHS 2014 dataset. Findings reveal that, the number of children increases with the increment of respondent ’s age but number of children declines if education status of respondents as well as their husbands’ increases. Similarly, religion, wealth index and wanted last child have significantly influenced the number of child ever born. Surprisingly, the number of children ever born to a mother from rur al area does not differ signif...
Source: Health Information Science and Systems - December 5, 2018 Category: Information Technology Source Type: research

An optimized Mamdani FPD controller design of cardiac pacemaker
AbstractCardiac pacemaker is a standard implantable medical electronic device for management and treatment of the heart rhythm disorders aiming to improved healthcare. Developing a new pacemaker based heart stimulation techniques has a vital role in preserving the patient ’s life. This target inspired the present work to design a new Mamdani fuzzy proportional–derivative (FPD) controller of a cardiac pacemaker, where Mamdani algorithm is the most common algorithm to deal with the human signals. The electrical pulses have closed features to the Sino atrial node pu lses, which are delivered to the patient’s...
Source: Health Information Science and Systems - November 28, 2018 Category: Information Technology Source Type: research

Neural networks for mining the associations between diseases and symptoms in clinical notes
AbstractThere are challenges for analyzing the narrative clinical notes in Electronic Health Records (EHRs) because of their unstructured nature. Mining the associations between the clinical concepts within the clinical notes can support physicians in making decisions, and provide researchers evidence about disease development and treatment. In this paper, in order to model and analyze disease and symptom relationships in the clinical notes, we present a concept association mining framework that is based on word embedding learned through neural networks. The approach is tested using 154,738 clinical notes from 500 patients...
Source: Health Information Science and Systems - November 28, 2018 Category: Information Technology Source Type: research

Automated emergency paramedical response system
AbstractWith the evolution of technology, the fields of medicine and science have also witnessed numerous advancements. In medical emergencies, a few minutes can be the difference between life and death. The obstacles encountered while providing medical assistance can be eliminated by ensuring quicker care and accessible systems. To this effect, the proposed end-to-end system —automated emergency paramedical response system (AEPRS) is semi-autonomous and utilizes aerial distribution by drones, for providing medical supplies on site in cases of paramedical emergencies as well as for patients with a standing history of...
Source: Health Information Science and Systems - November 13, 2018 Category: Information Technology Source Type: research

Centroid tracking and velocity measurement of white blood cell in video
AbstractAutomated blood cells tracking system has a vital role as the tracking process reflects the blood cell characteristics and indicates several diseases. Blood cells tracking is challenging due to the non-rigid shapes of the blood cells, and the variability in their videos along with the existence of different moving objects in the blood. To tackle such challenges, we proposed a green star based centroid (GSBC) moving white blood cell (WBC) tracking algorithm to measure its velocity and draw its trajectory. The proposed cell tracking system consists of two stages, namely WBC detection and blob analysis, and fine tunin...
Source: Health Information Science and Systems - November 1, 2018 Category: Information Technology Source Type: research

Ensemble of subspace discriminant classifiers for schistosomal liver fibrosis staging in mice microscopic images
AbstractSchistosomiasis is one of the dangerous parasitic diseases that affect the liver tissues leading to liver fibrosis. Such disease has several levels, which indicate the degree of fibrosis severity. To assess the fibrosis level for diagnosis and treatment, the microscopic images of the liver tissues were examined at their different stages. In the present work, an automated staging method is proposed to classify the statistical extracted features from each fibrosis stage using an ensemble classifier, namely the subspace ensemble using linear discriminant learning scheme. The performance of the subspace/discriminant en...
Source: Health Information Science and Systems - November 1, 2018 Category: Information Technology Source Type: research

Urate crystal deposition, prevention and various diagnosis techniques of GOUT arthritis disease: a comprehensive review
AbstractGout is described as difficult in joint sore, uttermost ordinarily in the principal metatarsophalangeal joint, attend from formation of urate monosodium crystallization in a joint space. Analysis might be affirmed by recognizable proof of urate monosodium precious stones in synovial liquid of the influenced joint. There has been expanded enthusiasm for gout in common scholarly and clinical practice settings. The pervasiveness of both hyperuricemia and gout has ascended as most recent decade of time in created nations and in this way weight of gout as expanded. The relationship of hyperuricemia and gout with cardio ...
Source: Health Information Science and Systems - October 8, 2018 Category: Information Technology Source Type: research

Transfer learning based histopathologic image classification for breast cancer detection
AbstractBreast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment. Thus, in recent years, early breast cancer detection systems based on patient ’s imagery are in demand. Deep learning attracts many researchers recently and many computer vision applications have come out in various environments. Convolutional neural network (CNN) which is known as deep learning architecture, has achieved impressive results in many applications. CNNs genera lly suffer from tuning a huge number of parameters which bring a great amount of ...
Source: Health Information Science and Systems - September 28, 2018 Category: Information Technology Source Type: research