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Journal of Medical Systems

Takuya Sakata, Kenji Araki, Tomoyoshi Yamazaki, Koichi Kawano, Minoru Maeda, Muneo Kushima, Sanae Araki
At the University of Miyazaki Hospital (UMH), we have accumulated and semantically structured a vast amount of medical information since the activation of the electronic health record system approximately 10 years ago. With this medical information, we have decided to develop an alert system for aiding in medical treatment. The purpose of this investigation is to not only to integrate an alert framework into the electronic heath record system, but also to formulate a modeling method of this knowledge. A trial alert framework was developed for the staff in various occupational categories at the UMH...
May 9, 2018: Journal of Medical Systems
Nathalia Yukie Crepaldi, Inacia Bezerra de Lima, Fernanda Bergamini Vicentine, Lídia Maria Lourençon Rodrigues, Tiago Lara Michelin Sanches, Antonio Ruffino-Netto, Domingos Alves, Rui Pedro Charters Lopes Rijo
Assessment of health information systems consider different aspects of the system itself. They focus or on the professional who will use the software or on its usability or on the software engineering metrics or on financial and managerial issues. The existent approaches are very resources consuming, disconnected, and not standardized. As the software becomes more critical in the health organizations and in patients, becoming used as a medical device or a medicine, there is an urgency to identify tools and methods that can be applied in the development process...
May 8, 2018: Journal of Medical Systems
Ahmad Firdaus, Nor Badrul Anuar, Mohd Faizal Ab Razak, Ibrahim Abaker Targio Hashem, Syafiq Bachok, Arun Kumar Sangaiah
The increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include root exploit, botnets, and Trojans and root exploit is one of the most dangerous malware. It compromises the operating system kernel in order to gain root privileges which are then used by attackers to bypass the security mechanisms, to gain complete control of the operating system, to install other possible types of malware to the devices, and finally, to steal victims' private keys linked to the blockchain...
May 4, 2018: Journal of Medical Systems
Mark T Seelen, Tynan H Friend, Wilton C Levine
The Massachusetts General Hospital (MGH) is merging its older endoscope processing facilities into a single new facility that will enable high-level disinfection of endoscopes for both the ORs and Endoscopy Suite, leveraging economies of scale for improved patient care and optimal use of resources. Finalized resource planning was necessary for the merging of facilities to optimize staffing and make final equipment selections to support the nearly 33,000 annual endoscopy cases. To accomplish this, we employed operations management methodologies, analyzing the physical process flow of scopes throughout the existing Endoscopy Suite and ORs and mapping the future state capacity of the new reprocessing facility...
May 4, 2018: Journal of Medical Systems
Roopa B Hegde, Keerthana Prasad, Harishchandra Hebbar, Brij Mohan Kumar Singh
Peripheral Blood Smear analysis plays a vital role in diagnosis of many diseases such as leukemia, anemia, malaria, lymphoma and infections. Unusual variations in color, shape and size of blood cells indicate abnormal condition. We used a total of 117 images from Leishman stained peripheral blood smears acquired at a magnification of 100X. In this paper we present a robust image processing algorithm for detection of nuclei and classification of white blood cells based on features of the nuclei. We used novel image enhancement method to manage illumination variations and TissueQuant method to manage color variations for the detection of nuclei...
May 2, 2018: Journal of Medical Systems
Jana Nowaková, Michal Prílepok, Václav Snášel
The article Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree, written by Jana Nowaková, Michal Prílepok and Václav Snášel, was originally published electronically on the publisher's internet portal (currently SpringerLink) on December 15, 2016 without open access.
May 2018: Journal of Medical Systems
Ateke Goshvarpour, Atefeh Goshvarpour
Heart rate variability (HRV) analysis has become a widely used tool for monitoring pathological and psychological states in medical applications. In a typical classification problem, information fusion is a process whereby the effective combination of the data can achieve a more accurate system. The purpose of this article was to provide an accurate algorithm for classifying HRV signals in various psychological states. Therefore, a novel feature level fusion approach was proposed. First, using the theory of information, two similarity indicators of the signal were extracted, including correntropy and Cauchy-Schwarz divergence...
April 30, 2018: Journal of Medical Systems
Anyembe Andrew Omala, Angolo Shem Mbandu, Kamenyi Domenic Mutiria, Chunhua Jin, Fagen Li
Wireless body area network (WBAN) provides a medium through which physiological information could be harvested and transmitted to application provider (AP) in real time. Integrating WBAN in a heterogeneous Internet of Things (IoT) ecosystem would enable an AP to monitor patients from anywhere and at anytime. However, the IoT roadmap of interconnected 'Things' is still faced with many challenges. One of the challenges in healthcare is security and privacy of streamed medical data from heterogeneously networked devices...
April 28, 2018: Journal of Medical Systems
Victor Koh, Issac Niwas Swamidoss, Maria Cecilia D Aquino, Paul T Chew, Chelvin Sng
Develop an algorithm to predict the success of laser peripheral iridotomy (LPI) in primary angle closure suspect (PACS), using pre-treatment anterior segment optical coherence tomography (ASOCT) scans. A total of 116 eyes with PACS underwent LPI and time-domain ASOCT scans (temporal and nasal cuts) were performed before and 1 month after LPI. All the post-treatment scans were classified to one of the following categories: (a) both angles open, (b) one of two angles open and (c) both angles closed. After LPI, success is defined as one or more angles changed from close to open...
April 27, 2018: Journal of Medical Systems
Mathias Paulo Loredo E Silva, Brenda Dutra de Souza Matos, Oscarina da Silva Ezequiel, Alessandra Lamas Granero Lucchetti, Giancarlo Lucchetti
The use of smartphones is revolutionizing the way information is acquired, leading to profound modifications in teaching medicine. Nevertheless, inadvertent use can negatively affect student learning. The present study aims to evaluate smartphone use in the educational context as well as Internet addiction and its repercussions on surface and deep learning and to compare them during the different phases of medical students' education. This is a cross-sectional study involving medical students in all phases of education...
April 26, 2018: Journal of Medical Systems
Yiqing Zhao, Nooshin J Fesharaki, Xiaohui Li, Timothy B Patrick, Jake Luo
Most current image retrieval methods require constructing semantic metadata for representing image content. To manually create semantic metadata for medical images is time-consuming, yet it is a crucial component for query expansion. We proposed a new method for searching medical image notes that uses semantic metadata to improve query expansion and leverages a knowledge model developed specifically for the medical image domain to create relevant metadata. We used a syntactic parser and the Unified Medical Language System to analyze the corpus and store text information as semantic metadata in a knowledge model...
April 25, 2018: Journal of Medical Systems
Erdenebayar Urtnasan, Jong-Uk Park, Eun-Yeon Joo, Kyoung-Joung Lee
In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers including activation, pooling, and dropout layers. One-dimensional (1D) convolution, rectified linear units (ReLU), and max pooling were applied to the convolution, activation, and pooling layers, respectively. For training and evaluation of the CNN model, a single-lead ECG dataset was collected from 82 subjects with OSA and was divided into training (including data from 63 patients with 34,281 events) and testing (including data from 19 patients with 8571 events) datasets...
April 23, 2018: Journal of Medical Systems
Kun-Chan Lan, Paweeya Raknim, Wei-Fong Kao, Jyh-How Huang
Heart rate variability (HRV) is often used to assess the risk of cardiovascular disease, and data on this can be obtained via electrocardiography (ECG). However, collecting heart rate data via photoplethysmography (PPG) is now a lot easier. We investigate the feasibility of using the PPG-based heart rate to estimate HRV and predict diseases. We obtain three months of PPG-based heart rate data from subjects with and without hypertension, and calculate the HRV based on various forms of time and frequency domain analysis...
April 21, 2018: Journal of Medical Systems
Ashish Kumar, Manjeet Kumar, Rama Komaragiri
Bradycardia can be modulated using the cardiac pacemaker, an implantable medical device which sets and balances the patient's cardiac health. The device has been widely used to detect and monitor the patient's heart rate. The data collected hence has the highest authenticity assurance and is convenient for further electric stimulation. In the pacemaker, ECG detector is one of the most important element. The device is available in its new digital form, which is more efficient and accurate in performance with the added advantage of economical power consumption platform...
April 19, 2018: Journal of Medical Systems
Pedro Nogueira, Joana Urbano, Luís Paulo Reis, Henrique Lopes Cardoso, Daniel Castro Silva, Ana Paula Rocha, Joaquim Gonçalves, Brígida Mónica Faria
With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health...
April 17, 2018: Journal of Medical Systems
Mohammad Mehedi Hassan, Shamsul Huda, Md Zia Uddin, Ahmad Almogren, Majed Alrubaian
In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities...
April 16, 2018: Journal of Medical Systems
Alberto Bellido, Pablo Ruisoto, Ana Beltran-Velasco, Vicente Javier Clemente-Suárez
The aim of this study is to review the current tools for the assessment of stress response in humans, ranging from the use of psychological questionnaires to the latest tools involving portable digital devices. Practical implications in educational context are further discussed.
April 16, 2018: Journal of Medical Systems
Saurabh Kumar Srivastava, Sandeep Kumar Singh, Jasjit S Suri
A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics. This research study proposes a concept of misrepresentation ratio (MRR) on input healthcare text data and models the PE criteria for validating the hypothesis...
April 13, 2018: Journal of Medical Systems
Shawne Olson, Stephanie Jaross, Gail S Rebischke-Smith, Frank Chivers, Stephanie K Covel, Carolyn E Millen
No abstract text is available yet for this article.
April 13, 2018: Journal of Medical Systems
Yu-Ning Yu, Faiyaz Doctor, Shou-Zen Fan, Jiann-Shing Shieh
During surgical procedures, bispectral index (BIS) is a well-known measure used to determine the patient's depth of anesthesia (DOA). However, BIS readings can be subject to interference from many factors during surgery, and other parameters such as blood pressure (BP) and heart rate (HR) can provide more stable indicators. However, anesthesiologist still consider BIS as a primary measure to determine if the patient is correctly anaesthetized while relaying on the other physiological parameters to monitor and ensure the patient's status is maintained...
April 13, 2018: Journal of Medical Systems
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