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Healthcare Informatics Research

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https://www.readbyqxmd.com/read/29770248/hedea-a-python-tool-for-extracting-and-analysing-semi-structured-information-from-medical-records
#1
Anshul Aggarwal, Sunita Garhwal, Ajay Kumar
Objectives: One of the most important functions for a medical practitioner while treating a patient is to study the patient's complete medical history by going through all records, from test results to doctor's notes. With the increasing use of technology in medicine, these records are mostly digital, alleviating the problem of looking through a stack of papers, which are easily misplaced, but some of these are in an unstructured form. Large parts of clinical reports are in written text form and are tedious to use directly without appropriate pre-processing...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770247/using-statistical-and-machine-learning-methods-to-evaluate-the-prognostic-accuracy-of-sirs-and-qsofa
#2
Akash Gupta, Tieming Liu, Scott Shepherd, William Paiva
Objectives: The objective of this study was to compare the performance of two popularly used early sepsis diagnostic criteria, systemic inflammatory response syndrome (SIRS) and quick Sepsis-related Organ Failure Assessment (qSOFA), using statistical and machine learning approaches. Methods: This retrospective study examined patient visits in Emergency Department (ED) with sepsis related diagnosis. The outcome was 28-day in-hospital mortality. Using odds ratio (OR) and modeling methods (decision tree [DT], multivariate logistic regression [LR], and naïve Bayes [NB]), the relationships between diagnostic criteria and mortality were examined...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770246/development-of-the-imb-model-and-an-evidence-based-diabetes-self-management-mobile-application
#3
Eunjoo Jeon, Hyeoun-Ae Park
Objectives: This study developed a diabetes self-management mobile application based on the information-motivation-behavioral skills (IMB) model, evidence extracted from clinical practice guidelines, and requirements identified through focus group interviews (FGIs) with diabetes patients. Methods: We developed a diabetes self-management (DSM) app in accordance with the following four stages of the system development life cycle. The functional and knowledge requirements of the users were extracted through FGIs with 19 diabetes patients...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770245/evaluation-of-the-ingval-pedobarography-system-for-monitoring-of-walking-speed
#4
Per Anders Rickard Hellstrom, Anna Åkerberg, Martin Ekström, Mia Folke
Objectives: Walking speed is an important component of movement and is a predictor of health in the elderly. Pedobarography, the study of forces acting between the plantar surface of the foot and a supporting surface, is an approach to estimating walking speed even when no global positioning system signal is available. The developed portable system, Identifying Velocity and Load (IngVaL), is a cost effective alternative to commercially available pedobarography systems because it only uses three force sensing resistors...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770244/predicting-length-of-stay-in-intensive-care-units-after-cardiac-surgery-comparison-of-artificial-neural-networks-and-adaptive-neuro-fuzzy-system
#5
Hamidreza Maharlou, Sharareh R Niakan Kalhori, Shahrbanoo Shahbazi, Ramin Ravangard
Objectives: Accurate prediction of patients' length of stay is highly important. This study compared the performance of artificial neural network and adaptive neuro-fuzzy system algorithms to predict patients' length of stay in intensive care units (ICU) after cardiac surgery. Methods: A cross-sectional, analytical, and applied study was conducted. The required data were collected from 311 cardiac patients admitted to intensive care units after surgery at three hospitals of Shiraz, Iran, through a non-random convenience sampling method during the second quarter of 2016...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770243/mobile-technology-in-undergraduate-nursing-education-a-systematic-review
#6
Hyejung Lee, Haeyoung Min, Su-Mi Oh, Kaka Shim
Objectives: This study aimed to identify and systematically review the literature on the use of mobile technology in nursing education. The research findings could evidence the effectiveness of mobile technology in undergraduate nursing students' learning outcomes. Methods: Computerized searches were conducted using the Ovid-MEDLINE, Ovid-EMBASE, Cochrane Library, and CINAHL databases for relevant primary studies and limited to those between 2000 and February 2018...
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29770242/healthcare-informatics-research-s-journey-of-paving-the-road-to-excellence-in-global-healthcare-informatics
#7
EDITORIAL
Mona Choi, Jung A Kim
No abstract text is available yet for this article.
April 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503758/correction-development-and-evaluation-of-an-obesity-ontology-for-social-big-data-analysis
#8
Ae Ran Kim, Hyeoun-Ae Park, Tae-Min Song
[This corrects the article on p. 159 in vol. 23, PMID: 28875050.].
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503757/applying-deep-learning-in-medical-images-the-case-of-bone-age-estimation
#9
Jang Hyung Lee, Kwang Gi Kim
Objectives: A diagnostic need often arises to estimate bone age from X-ray images of the hand of a subject during the growth period. Together with measured physical height, such information may be used as indicators for the height growth prognosis of the subject. We present a way to apply the deep learning technique to medical image analysis using hand bone age estimation as an example. Methods: Age estimation was formulated as a regression problem with hand X-ray images as input and estimated age as output...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503756/customer-discovery-as-the-first-essential-step-for-successful-health-information-technology-system-development
#10
Punyotai Thamjamrassri, YuJin Song, JaeHyun Tak, HoYong Kang, Hyoun-Joong Kong, Jeeyoung Hong
Objectives: Customer discovery (CD) is a method to determine if there are actual customers for a product/service and what they would want before actually developing the product/service. This concept, however, is rather new to health information technology (IT) systems. Therefore, the aim of this paper was to demonstrate how to use the CD method in developing a comprehensive health IT service for patients with knee/leg pain. Methods: We participated in a 6-week I-Corps program to perform CD, in which we interviewed 55 people in person, by phone, or by video conference within 6 weeks: 4 weeks in the United States and 2 weeks in Korea...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503755/effects-of-flipped-learning-using-online-materials-in-a-surgical-nursing-practicum-a-pilot-stratified-group-randomized-trial
#11
Myung Kyung Lee, Bu Kyung Park
Objectives: This study examined the effect of flipped learning in comparison to traditional learning in a surgical nursing practicum. Methods: The subjects of this study were 102 nursing students in their third year of university who were scheduled to complete a clinical nursing practicum in an operating room or surgical unit. Participants were randomly assigned to either a flipped learning group (n = 51) or a traditional learning group (n = 51) for the 1-week, 45-hour clinical nursing practicum...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503754/trends-in-research-on-the-security-of-medical-information-in-korea-focused-on-information-privacy-security-in-hospitals
#12
Yong-Woon Kim, Namin Cho, Hye-Jung Jang
Objectives: Information technology involves a risk of privacy violation in providing easy access to confidential information,such as personal information and medical information through the Internet. In this study, we investigated medical information security to gain a better understanding of trends in research related to medical information security. Methods: We researched papers published on '의료정보' and 'medical information' in various Korean journals during a 10-year period from 2005 to 2015...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503753/automatic-glaucoma-detection-method-applying-a-statistical-approach-to-fundus-images
#13
Anindita Septiarini, Dyna M Khairina, Awang H Kridalaksana, Hamdani Hamdani
Objectives: Glaucoma is an incurable eye disease and the second leading cause of blindness in the world. Until 2020, the number of patients of this disease is estimated to increase. This paper proposes a glaucoma detection method using statistical features and the k-nearest neighbor algorithm as the classifier. Methods: We propose three statistical features, namely, the mean, smoothness and 3rd moment, which are extracted from images of the optic nerve head. These three features are obtained through feature extraction followed by feature selection using the correlation feature selection method...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503752/comparison-and-analysis-of-iso-ieee-11073-ihe-pcd-01-and-hl7-fhir-messages-for-personal-health-devices
#14
Sungkee Lee, Hyoungho Do
Objectives: Increasing use of medical devices outside of healthcare facilities inevitably requires connectivity and interoperability between medical devices and healthcare information systems. To this end, standards have been developed and used to provide interoperability between personal health devices (PHDs) and external systems. ISO/IEEE 11073 standards and IHE PCD-01 standard messages have been used the most in the exchange of observation data of health devices. Recently, transmitting observation data using the HL7 FHIR standard has been devised in the name of DoF (Devices on FHIR) and adopted very fast...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503751/evaluating-the-dietary-and-nutritional-apps-in-the-google-play-store
#15
Harleigh Schumer, Chioma Amadi, Ashish Joshi
Objectives: The objective of this study was to evaluate the features of diet and nutrition apps available in the Google Play Store. Methods: A search was conducted in August 2017 using the Google Play Store database to identify apps related to diet and nutrition. Terms entered into the app search engine included 'diet apps' and 'nutrition apps'. The first 50 apps resulting from each search term was assessed. Duplicates were removed, and a comparative analysis was performed on the remaining diet and nutrition apps...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503750/comparison-of-models-for-the-prediction-of-medical-costs-of-spinal-fusion-in-taiwan-diagnosis-related-groups-by-machine-learning-algorithms
#16
Ching-Yen Kuo, Liang-Chin Yu, Hou-Chaung Chen, Chien-Lung Chan
Objectives: The aims of this study were to compare the performance of machine learning methods for the prediction of the medical costs associated with spinal fusion in terms of profit or loss in Taiwan Diagnosis-Related Groups (Tw-DRGs) and to apply these methods to explore the important factors associated with the medical costs of spinal fusion. Methods: A data set was obtained from a regional hospital in Taoyuan city in Taiwan, which contained data from 2010 to 2013 on patients of Tw-DRG49702 (posterior and other spinal fusion without complications or comorbidities)...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503749/bayesian-based-decision-support-system-for-assessing-the-needs-for-orthodontic-treatment
#17
Bhornsawan Thanathornwong
Objectives: In this study, a clinical decision support system was developed to help general practitioners assess the need for orthodontic treatment in patients with permanent dentition. Methods: We chose a Bayesian network (BN) as the underlying model for assessing the need for orthodontic treatment. One thousand permanent dentition patient data sets chosen from a hospital record system were prepared in which one data element represented one participant with information for all variables and their stated need for orthodontic treatment...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503748/scenario-based-assessment-of-user-needs-for-point-of-care-robots
#18
Hyeong Suk Lee, Jeongeun Kim
Objectives: This study aimed to derive specific user requirements and barriers in a real medical environment to define the essential elements and functions of two types of point-of-care (POC) robot: a telepresence robot as a tool for teleconsultation, and a bedside robot to provide emotional care for patients. Methods: An analysis of user requirements was conducted; user needs were gathered and identified, and detailed, realistic scenarios were created. The prototype robots were demonstrated in physical environments for envisioning and evaluation...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503747/enchanted-life-space-adding-value-to-smart-health-by-integrating-human-desires
#19
REVIEW
Joohyun Kim, Hye Jin Kam, Yu Rang Park, Soyoung Yoo, Ji Seon Oh, Young-Hak Kim, Jae-Ho Lee
Objectives: Developments in advanced technology have unlocked an era of smart health, transforming healthcare practices inside and outside hospitals for both medical staff and patients. It is now possible for patients to collect detailed health data using smartphones and wearable devices, regardless of their physical location or time zone. The use of these patient-generated data holds great promise for future healthcare advancements in many ways; however, current strategies for smart-health technologies tend to focus on the smartness of the technology itself and on managing a particular disease or condition...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29503746/a-new-online-journal-management-system
#20
EDITORIAL
Hyejung Chang, Hyoun-Joong Kong
No abstract text is available yet for this article.
January 2018: Healthcare Informatics Research
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