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Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs
ConclusionsBy augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - November 1, 2017 Category: Information Technology Source Type: research

A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm
AbstractMicroaneurysms (MAs) are known as early signs of diabetic-retinopathy which are called red lesions in color fundus images. Detection of MAs in fundus images needs highly skilled physicians or eye angiography. Eye angiography is an invasive and expensive procedure. Therefore, an automatic detection system to identify the MAs locations in fundus images is in demand. In this paper, we proposed a system to detect the MAs in colored fundus images. The proposed method composed of three stages. In the first stage, a series of pre-processing steps are used to make the input images more convenient for MAs detection. To this...
Source: Health Information Science and Systems - November 1, 2017 Category: Information Technology Source Type: research

Supporting breast cancer decisions using formalized guidelines and experts decision patterns: initial prototype and evaluation
AbstractTransparent decisions and its documentation of breast cancer patients ’ therapy are getting more important especially since modern therapeutic approaches favor personalized forms of treatment. The medical decisions for a treatment are very complex, because there are rules and different options for each patient. To support the decision process, we analyzed the curren t decision rules and implemented them in a prototype of a rule-based expert system. Thus, this system shall support the quality assurance regarding transparent documentation of individualized therapeutic decisions. For evaluating the system, we used d...
Source: Health Information Science and Systems - October 30, 2017 Category: Information Technology Source Type: research

Statistical sleep pattern modelling for sleep quality assessment based on sound events
AbstractA good sleep is important for a healthy life. Recently, several consumer sleep devices have emerged on the market claiming that they can provide personal sleep monitoring; however, many of them require additional hardware or there is a lack of scientific evidence regarding their reliability. In this paper we proposed a novel method to assess the sleep quality through sound events recorded in the bedroom. We used subjective sleep quality as training label, combined several machine learning approaches including kernelized self organizing map, hierarchical clustering and hidden Markov model, obtained the models to ind...
Source: Health Information Science and Systems - October 30, 2017 Category: Information Technology Source Type: research

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine
ConclusionBasal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 30, 2017 Category: Information Technology Source Type: research

Classification of amyotrophic lateral sclerosis disease based on convolutional neural network and reinforcement sample learning algorithm
AbstractElectromyogram (EMG) signals contain useful information of the neuromuscular diseases like amyotrophic lateral sclerosis (ALS). ALS is a well-known brain disease, which can progressively degenerate the motor neurons. In this paper, we propose a deep learning based method for efficient classification of ALS and normal EMG signals. Spectrogram, continuous wavelet transform (CWT), and smoothed pseudo Wigner –Ville distribution (SPWVD) have been employed for time–frequency (T–F) representation of EMG signals. A convolutional neural network is employed to classify these features. In it, Two convolution layers, two...
Source: Health Information Science and Systems - October 30, 2017 Category: Information Technology Source Type: research

Using neutrosophic graph cut segmentation algorithm for qualified rendering image selection in thyroid elastography video
AbstractRecently, elastography has become very popular in clinical investigation for thyroid cancer detection and diagnosis. In elastogram, the stress results of the thyroid are displayed using pseudo colors. Due to variation of the rendering results in different frames, it is difficult for radiologists to manually select the qualified frame image quickly and efficiently. The purpose of this study is to find the qualified rendering result in the thyroid elastogram. This paper employs an efficient thyroid ultrasound image segmentation algorithm based on neutrosophic graph cut to find the qualified rendering images. Firstly,...
Source: Health Information Science and Systems - October 27, 2017 Category: Information Technology Source Type: research

An optimum allocation sampling based feature extraction scheme for distinguishing seizure and seizure-free EEG signals
AbstractEpileptic seizure is the common neurological disorder, which is generally identified by electroencephalogram (EEG) signals. In this paper, a new feature extraction methodology based on optimum allocation sampling (OAS) and Teager energy operator (TEO) is proposed for detection of seizure EEG signals. The OAS scheme selects the finite length homogeneous sequence from non-homogeneous recorded EEG signal. The trend of selected sequence by OAS is still non-linear, which is analyzed by non-linear operator TEO. The TEO convert non-linear but homogenous EEG sequence into amplitude –frequency modulated (AM–FM) componen...
Source: Health Information Science and Systems - October 27, 2017 Category: Information Technology Source Type: research

The potential adoption benefits and challenges of LOINC codes in a laboratory department: a case study
ConclusionIn this paper, we intend to provide a snapshot of the possible usage of LOINC codes in rural hospitals in low- and middle-income countries via simpler and detailed use cases. Our analysis may aid policymakers to gain a deeper understanding of LOINC codes in regard to clinical, administrative, and operational aspect and to make better-informed decisions in regard to LOINC codes adoption. The use case analysis also can be used by information system designers and developers to reference workflow within a laboratory department. We recognize that this manuscript is only a case study and that the exact steps and workfl...
Source: Health Information Science and Systems - October 11, 2017 Category: Information Technology Source Type: research

Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data
ConclusionsThis paper demonstrates that an ensemble classifier, DMT, is more robust in classifying noisy data than other widely used ensemble methods. DMT works on the data set that supports multiple simple trees. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 10, 2017 Category: Information Technology Source Type: research

Improving patient engagement in self-measured blood pressure monitoring using a mobile health technology
ConclusionsWe show significant decrease in BP with improved metrics over time. Higher engagement was associated with greater BP reduction and engagement was higher among those with greater clinical need of BP control.Practice implicationsHello Heart represents an operational mHealth technology to improve patient engagement and clinical outcomes. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - October 7, 2017 Category: Information Technology Source Type: research

Mining comorbidity patterns using retrospective analysis of big collection of outpatient records
ConclusionExplicating maximal frequent itemsets enables to build hypotheses concerning the relationships between the exogeneous and endogeneous factors triggering the formation of these sets. MixCO will help to identify risk groups of patients with a predisposition to develop socially-significant disorders like diabetes. This will turn static archives like the Diabetes Register in Bulgaria to a powerful alerting and predictive framework. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - September 28, 2017 Category: Information Technology Source Type: research

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection
ConclusionsThis is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - September 27, 2017 Category: Information Technology Source Type: research

Patient healthcare trajectory. An essential monitoring tool: a systematic review
ConclusionThis literature review highlights the recent interest in the trajectory concept. The approach is also gradually being used to monitor trajectories of care for chronic diseases such as diabetes, organ failure or coronary artery and MI trajectory of care, to improve care and reduce costs. Patient trajectory is undoubtedly an essential approach to be further explored in order to improve healthcare monitoring. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - April 12, 2017 Category: Information Technology Source Type: research

PredicT-ML: a tool for automating machine learning model building with big clinical data
Conclusions PredicT-ML will open the use of big clinical data to thousands of healthcare administrators and researchers and increase the ability to advance clinical research and improve healthcare. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 7, 2016 Category: Information Technology Source Type: research