Fundus image is important for the medical screening and diagnosis of variety ophthalmopathy. The effectiveness of such a process, however, depends very much on the quality of the fundus image captured. This paper aims to asses in real-time the quality of a fundus image by first extracting a multitude of generic features, including statistical characteristics, entropy, texture, symmetry, frequency components and blur metric, which is then followed by a support vector machine (SVM) trained to filter out the poor quality image for clinic usage. The method was tested on a dataset of 3224 images collected from an eye hospital's practical screening project in rural areas in Northeastern Region of China. With the detection rate achieved being 0.9308, the corresponding false alarm rate is 0.1127, and the overall accuracy is 0.9138. The area under an ROC curve is as high as 0.9619. It is shown that the fundus images of poor quality can be automatically detected on the spot to ensure a clinically meaningful ophthalmopathy screening and diagnosis by a human expert or even an artificial intelligence software.
{"title":"Generic features for fundus image quality evaluation","authors":"Zhen-Jie Yao, Zhi-Peng Zhang, Li-Qun Xu, Qingxia Fan, Ling Xu","doi":"10.1109/HealthCom.2016.7749522","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749522","url":null,"abstract":"Fundus image is important for the medical screening and diagnosis of variety ophthalmopathy. The effectiveness of such a process, however, depends very much on the quality of the fundus image captured. This paper aims to asses in real-time the quality of a fundus image by first extracting a multitude of generic features, including statistical characteristics, entropy, texture, symmetry, frequency components and blur metric, which is then followed by a support vector machine (SVM) trained to filter out the poor quality image for clinic usage. The method was tested on a dataset of 3224 images collected from an eye hospital's practical screening project in rural areas in Northeastern Region of China. With the detection rate achieved being 0.9308, the corresponding false alarm rate is 0.1127, and the overall accuracy is 0.9138. The area under an ROC curve is as high as 0.9619. It is shown that the fundus images of poor quality can be automatically detected on the spot to ensure a clinically meaningful ophthalmopathy screening and diagnosis by a human expert or even an artificial intelligence software.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129319816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749519
Bonnie K. MacKellar, Christina Schweikert
Patients with serious diseases, such as cancer, often must consider and choose between multiple clinical trials. Patients are often concerned that participation in one clinical trial may preclude their participation in another trial. We are developing a system to help patients in this decision making process, focusing on pediatric cancer where clinical trial participation is very high. In this paper, we present a detailed description of the approach used to process and analyze the eligibility constraints, using a pattern-based approach from the literature. We show how the semantic categorizations produced by these patterns can be used to determine which eligibility constraints can produce conflicts, as well as to guide an analysis algorithm. This work contributes to research on using eligibility criteria and other clinical trial information to better support patient decision making and to improve accrual of patients into clinical trials.
{"title":"Patterns for conflict identification in clinical trial eligibility criteria","authors":"Bonnie K. MacKellar, Christina Schweikert","doi":"10.1109/HealthCom.2016.7749519","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749519","url":null,"abstract":"Patients with serious diseases, such as cancer, often must consider and choose between multiple clinical trials. Patients are often concerned that participation in one clinical trial may preclude their participation in another trial. We are developing a system to help patients in this decision making process, focusing on pediatric cancer where clinical trial participation is very high. In this paper, we present a detailed description of the approach used to process and analyze the eligibility constraints, using a pattern-based approach from the literature. We show how the semantic categorizations produced by these patterns can be used to determine which eligibility constraints can produce conflicts, as well as to guide an analysis algorithm. This work contributes to research on using eligibility criteria and other clinical trial information to better support patient decision making and to improve accrual of patients into clinical trials.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"31 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114102557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749487
Y. Yun, I. Gu
This paper addresses the problem of classifying activities of daily living in video. The proposed method uses a tree structure of two layers, where in each node of the tree there resides a Riemannian manifold that corresponds to different part-based covariance features. In the first layer, activities are classified according to the dynamics of upper body parts. In the second layer, activities are further classified according to the appearance of local image patches at hands in key frames, where the interacting objects are likely to be attached. The novelties of this paper include: (i) characterizing the motion of upper body parts by a covariance matrix of distances between each pair of key points and the orientations of lines that connect them; (ii) describing human-object interaction by the appearance of local regions around hands in key frames that are selected based on the proximity of hands to other key points; (iii) formulating a pairwise geodesics-based kernel for activity classification on Riemannian manifolds under the log-Euclidean metric. Experiments were conducted on a video dataset containing a total number of 426 video events (activities) from 4 classes. The proposed method is shown to be effective by achieving high classification accuracy (93.79% on average) and small false alarms (1.99% on average) overall, as well as for each individual class.
{"title":"Exploiting riemannian manifolds for daily activity classification in video towards health care","authors":"Y. Yun, I. Gu","doi":"10.1109/HealthCom.2016.7749487","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749487","url":null,"abstract":"This paper addresses the problem of classifying activities of daily living in video. The proposed method uses a tree structure of two layers, where in each node of the tree there resides a Riemannian manifold that corresponds to different part-based covariance features. In the first layer, activities are classified according to the dynamics of upper body parts. In the second layer, activities are further classified according to the appearance of local image patches at hands in key frames, where the interacting objects are likely to be attached. The novelties of this paper include: (i) characterizing the motion of upper body parts by a covariance matrix of distances between each pair of key points and the orientations of lines that connect them; (ii) describing human-object interaction by the appearance of local regions around hands in key frames that are selected based on the proximity of hands to other key points; (iii) formulating a pairwise geodesics-based kernel for activity classification on Riemannian manifolds under the log-Euclidean metric. Experiments were conducted on a video dataset containing a total number of 426 video events (activities) from 4 classes. The proposed method is shown to be effective by achieving high classification accuracy (93.79% on average) and small false alarms (1.99% on average) overall, as well as for each individual class.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114725624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749491
Abdulwahab Sahyoun, Karim Chehab, O. Al-Madani, F. Aloul, A. Sagahyroon
This paper aims to provide a Parkinson's Disease (PD) symptoms assessment tool using an Android smartphone application that allows PD patients to assess their symptoms using both quantitative and qualitative tests. Simple touch screen and motion tests focus on objectively measuring PD symptoms, whereas a questionnaire targets the subjective ones. The concatenation of the collected results will allow the application to accurately target several PD symptoms without visual or traditional assessment. Physicians, hospitals, and clinics will then be able to receive this data over the network for further assessment, analysis, and research. This enables the self-monitoring of patients, as well as remote monitoring from physicians in clinics and hospitals. In addition to this, this application aims to expand PD research and provide improvements to the current treatment process. Ultimately, the aim is to enable thousands of people, anywhere and at any time, to easily diagnose and assess the PD before visiting a specialist.
{"title":"ParkNosis: Diagnosing Parkinson's disease using mobile phones","authors":"Abdulwahab Sahyoun, Karim Chehab, O. Al-Madani, F. Aloul, A. Sagahyroon","doi":"10.1109/HealthCom.2016.7749491","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749491","url":null,"abstract":"This paper aims to provide a Parkinson's Disease (PD) symptoms assessment tool using an Android smartphone application that allows PD patients to assess their symptoms using both quantitative and qualitative tests. Simple touch screen and motion tests focus on objectively measuring PD symptoms, whereas a questionnaire targets the subjective ones. The concatenation of the collected results will allow the application to accurately target several PD symptoms without visual or traditional assessment. Physicians, hospitals, and clinics will then be able to receive this data over the network for further assessment, analysis, and research. This enables the self-monitoring of patients, as well as remote monitoring from physicians in clinics and hospitals. In addition to this, this application aims to expand PD research and provide improvements to the current treatment process. Ultimately, the aim is to enable thousands of people, anywhere and at any time, to easily diagnose and assess the PD before visiting a specialist.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115778226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749500
Arshia A. Khan, M. Reuter, N. Phung, Syed S. Hafeez
Pressure ulcers pose a huge financial burden on the economy. Pressure ulcers cost between $9.1 to 11.6 billion a year in the United States. Each individual pressure can cost from $20,900 to $151,700 per pressure ulcer. Wheelchair users with spinal cord injury have a higher risk of developing pressure ulcers due to limited mobility and the countless hours they spend in the wheelchair, exerting pressure on the points of interface between the bony structure and the wheelchair cushion. The areas of interface that are under prolonged pressure lack blood flow, causing the tissue to breakdown, leading to a decubitus or pressure ulcer. Approximately 28.9 % wheelchair users in communities, 27% in nursing homes, and between 5 and 30% of hospitalized patients develop pressure sores. Nearly 70% of elderly patients develop pressure ulcers, which in turn significantly increase the healthcare management and costs and can be a cause of pain, discomfort, loss of independence and mobility in not only the elderly but also the younger patients. Mobile technology can be exploited to provide a technological solution to preventing pressure ulcers. An app was designed and developed to notify, walk through the process of weight shifting and also track the movements of the patient performing weight shifting using the accelerometer. The app was tested to find that the forward lean movements can be tracked accurately using the accelerometer but the lateral movements although tracked could not verify that the weight shifting was correctly performed. In order to fix this issue the pressure map is used as an additional sensor to track and monitor the weight shifting accurately. This paper discusses the design and development of the app in two phases.
{"title":"Wireless solution to prevent decubitus ulcers: Preventive weight shifting guide, monitor, and tracker app for wheel chair users with spinal cord injuries (phase II)","authors":"Arshia A. Khan, M. Reuter, N. Phung, Syed S. Hafeez","doi":"10.1109/HealthCom.2016.7749500","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749500","url":null,"abstract":"Pressure ulcers pose a huge financial burden on the economy. Pressure ulcers cost between $9.1 to 11.6 billion a year in the United States. Each individual pressure can cost from $20,900 to $151,700 per pressure ulcer. Wheelchair users with spinal cord injury have a higher risk of developing pressure ulcers due to limited mobility and the countless hours they spend in the wheelchair, exerting pressure on the points of interface between the bony structure and the wheelchair cushion. The areas of interface that are under prolonged pressure lack blood flow, causing the tissue to breakdown, leading to a decubitus or pressure ulcer. Approximately 28.9 % wheelchair users in communities, 27% in nursing homes, and between 5 and 30% of hospitalized patients develop pressure sores. Nearly 70% of elderly patients develop pressure ulcers, which in turn significantly increase the healthcare management and costs and can be a cause of pain, discomfort, loss of independence and mobility in not only the elderly but also the younger patients. Mobile technology can be exploited to provide a technological solution to preventing pressure ulcers. An app was designed and developed to notify, walk through the process of weight shifting and also track the movements of the patient performing weight shifting using the accelerometer. The app was tested to find that the forward lean movements can be tracked accurately using the accelerometer but the lateral movements although tracked could not verify that the weight shifting was correctly performed. In order to fix this issue the pressure map is used as an additional sensor to track and monitor the weight shifting accurately. This paper discusses the design and development of the app in two phases.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115784172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749524
T. Godinho, Eduardo Almeida, Luís Bastião, C. Costa
Nowadays, medical imaging laboratories are supported by heterogeneous systems, including image repositories, acquisition devices, viewer workstations and other administrative information systems. They hold tremendous amounts of data resulting not only from imaging modalities, but also from patient diagnosis, treatment, and services management. Unfortunately, the interoperability between the different medical information systems is still a major limitation. Despite the existence of standards to support the distinct RIS and PACS applications, such as DICOM and HL7, the interoperability between them is, in most cases, limited to a few sets of information elements. As a result, the establishment of cooperative workflows or the integrated visualization of patient data is still compromised. Moreover, this scenario severely constraints the usage of these data for research and business analytics purposes, commonly referred as secondary uses of data. In this document, we propose a method for transforming echocardiography reports held by proprietary information systems into DICOM Structured Reports (SR), the gold standard for interoperability in medical imaging. As a result, reports, images, and associated metadata can be accessed and shared by all PACS applications in an integrated and structured manner. Furthermore, the large-scale federation of those elements has a tremendous interest for data analytics and secondary uses of data.
{"title":"Integrating multiple data sources in a cardiology imaging laboratory","authors":"T. Godinho, Eduardo Almeida, Luís Bastião, C. Costa","doi":"10.1109/HealthCom.2016.7749524","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749524","url":null,"abstract":"Nowadays, medical imaging laboratories are supported by heterogeneous systems, including image repositories, acquisition devices, viewer workstations and other administrative information systems. They hold tremendous amounts of data resulting not only from imaging modalities, but also from patient diagnosis, treatment, and services management. Unfortunately, the interoperability between the different medical information systems is still a major limitation. Despite the existence of standards to support the distinct RIS and PACS applications, such as DICOM and HL7, the interoperability between them is, in most cases, limited to a few sets of information elements. As a result, the establishment of cooperative workflows or the integrated visualization of patient data is still compromised. Moreover, this scenario severely constraints the usage of these data for research and business analytics purposes, commonly referred as secondary uses of data. In this document, we propose a method for transforming echocardiography reports held by proprietary information systems into DICOM Structured Reports (SR), the gold standard for interoperability in medical imaging. As a result, reports, images, and associated metadata can be accessed and shared by all PACS applications in an integrated and structured manner. Furthermore, the large-scale federation of those elements has a tremendous interest for data analytics and secondary uses of data.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127834492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749426
C. Wickramage, T. Sahama, C. Fidge
Due to the growing use of digital technologies and Electronic Health Record systems, new auditing mechanisms are needed to help protect stakeholders from information misuse, both deliberate and accidental. Electronic storage of health records and use of sensor networks, wearable and ubiquitous health tracking devices raise numerous privacy related threats for both healthcare providers and their patients. A purely preventive approach to information access is not appropriate in healthcare scenarios, especially during emergencies, so after-the-fact justifications are needed to manage information handling risks in such an environment. To allow such justifications we need to analyse the root causes for unusual human actions or behaviours but current system event logs are inadequate for this purpose. Hence, a better solution would be to generate audit logs sufficient for analysing information use anomalies. Here we explain the limitations of existing event logs in clinical settings when attempting to perform after-the-fact justifications as part of a clinical Information Accountability system. From this we recommend additional features that must be added to event logs to support a healthcare-based Information Accountability Framework.
{"title":"Anatomy of log files: Implications for information accountability measures","authors":"C. Wickramage, T. Sahama, C. Fidge","doi":"10.1109/HealthCom.2016.7749426","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749426","url":null,"abstract":"Due to the growing use of digital technologies and Electronic Health Record systems, new auditing mechanisms are needed to help protect stakeholders from information misuse, both deliberate and accidental. Electronic storage of health records and use of sensor networks, wearable and ubiquitous health tracking devices raise numerous privacy related threats for both healthcare providers and their patients. A purely preventive approach to information access is not appropriate in healthcare scenarios, especially during emergencies, so after-the-fact justifications are needed to manage information handling risks in such an environment. To allow such justifications we need to analyse the root causes for unusual human actions or behaviours but current system event logs are inadequate for this purpose. Hence, a better solution would be to generate audit logs sufficient for analysing information use anomalies. Here we explain the limitations of existing event logs in clinical settings when attempting to perform after-the-fact justifications as part of a clinical Information Accountability system. From this we recommend additional features that must be added to event logs to support a healthcare-based Information Accountability Framework.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124084307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749520
A. Khalil, Y. Liew, S. Ng, K. Lai, Y. Hum
This study proposes a registration framework to register 2D echocardiography images with cardiac CT volume. The registration realizes the fusion of CT and echocardiography with the aim to aid the diagnosis of cardiac diseases. The image registration framework consists of two major steps: temporal and spatial registration. Temporal registration utilizes the ECG data to identify frames at similar cardiac phase as the CT volume. Spatial registration is an intensity-based normalized mutual information (NMI) method applied with pattern search optimization algorithm to produce interpolated cardiac CT image that matches the echocardiography image. Our proposed registration method has been applied on the short axis "Mercedes Benz" sign view of the aortic valve. The accuracy of our fully automated registration method were 0.81 ± 0.08 and 1.30 ± 0.13 mm in terms of Dice coefficient and Hausdorff distance. This accuracy is comparable to gold standard manual registration by expert. There was no significant difference in aortic annulus diameter measurement between the automatically and manually registered CT images. Without the use of optical tracking, we have shown the applicability of this technique for effective registration of echocardiography with cardiac CT volume.
{"title":"Echocardiography to cardiac CT image registration: Spatial and temporal registration of the 2D planar echocardiography images with cardiac CT volume","authors":"A. Khalil, Y. Liew, S. Ng, K. Lai, Y. Hum","doi":"10.1109/HealthCom.2016.7749520","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749520","url":null,"abstract":"This study proposes a registration framework to register 2D echocardiography images with cardiac CT volume. The registration realizes the fusion of CT and echocardiography with the aim to aid the diagnosis of cardiac diseases. The image registration framework consists of two major steps: temporal and spatial registration. Temporal registration utilizes the ECG data to identify frames at similar cardiac phase as the CT volume. Spatial registration is an intensity-based normalized mutual information (NMI) method applied with pattern search optimization algorithm to produce interpolated cardiac CT image that matches the echocardiography image. Our proposed registration method has been applied on the short axis \"Mercedes Benz\" sign view of the aortic valve. The accuracy of our fully automated registration method were 0.81 ± 0.08 and 1.30 ± 0.13 mm in terms of Dice coefficient and Hausdorff distance. This accuracy is comparable to gold standard manual registration by expert. There was no significant difference in aortic annulus diameter measurement between the automatically and manually registered CT images. Without the use of optical tracking, we have shown the applicability of this technique for effective registration of echocardiography with cardiac CT volume.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126153497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749501
A. Idri, M. Bachiri, J. Alemán, J. Álvarez
In order to improve the management of the patients' health data and promote the exchange between the patients and healthcare providers, mobile personal health records (mPHRs), as mobile applications, are used to access, store and manage these data. In this paper, a design of the software quality evaluation of free mPHRs for pregnancy monitoring is introduced. Ten mobile applications (4 for iOS and 6 for Android) are selected for the evaluation. A list of tasks is set to be executed in order to answer a quality assessment questionnaire that is developed for this purpose, covering the four quality characteristics: Functional suitability, Operability, Performance efficiency and Reliability, by using the ISO/IEC 25010 quality standard. This evaluation aims to analyze the degree of meeting these quality characteristics, in addition to the compliance between the users' ratings in the apps stores and the fulfillment of the quality characteristics by the mPHRs for pregnancy monitoring. This study is intended to be developed by conducting the proposed design of the evaluation, which will be of great use for the developers of these apps for further improvements.
{"title":"Experiment design of free pregnancy monitoring mobile personal health records quality evaluation","authors":"A. Idri, M. Bachiri, J. Alemán, J. Álvarez","doi":"10.1109/HealthCom.2016.7749501","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749501","url":null,"abstract":"In order to improve the management of the patients' health data and promote the exchange between the patients and healthcare providers, mobile personal health records (mPHRs), as mobile applications, are used to access, store and manage these data. In this paper, a design of the software quality evaluation of free mPHRs for pregnancy monitoring is introduced. Ten mobile applications (4 for iOS and 6 for Android) are selected for the evaluation. A list of tasks is set to be executed in order to answer a quality assessment questionnaire that is developed for this purpose, covering the four quality characteristics: Functional suitability, Operability, Performance efficiency and Reliability, by using the ISO/IEC 25010 quality standard. This evaluation aims to analyze the degree of meeting these quality characteristics, in addition to the compliance between the users' ratings in the apps stores and the fulfillment of the quality characteristics by the mPHRs for pregnancy monitoring. This study is intended to be developed by conducting the proposed design of the evaluation, which will be of great use for the developers of these apps for further improvements.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128394455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749521
Roland Ellerweg, Dominic Reuter, Phil Weir
In teleradiology doctors view the image data of a healthcare institution from a remote site. To do so they typically connect to an image repository, download the necessary data and finally view it in a locally installed DICOM viewer. Recent research activities in teleradiology [1, 2, 3, 4] focus on the implementation of ubiquitously accessible web-based DICOM viewers which simplify the access and the collaboration among radiologists. However, these solutions either have a weak performance, they run on the client side only, or they are not as feature rich as their desktop counterpart. In this contribution we present an architecture of a web based DICOM viewer which has both, good performance as well as advanced features such as the visualization of anatomical structures. On the client side only native web technologies are used. The whole architecture has been implemented and evaluated in the GoSmart environment, a planning tool for minimally invasive cancer treatment.
{"title":"Architecture of a web-based DICOM viewer showing segmentations and simulations","authors":"Roland Ellerweg, Dominic Reuter, Phil Weir","doi":"10.1109/HealthCom.2016.7749521","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749521","url":null,"abstract":"In teleradiology doctors view the image data of a healthcare institution from a remote site. To do so they typically connect to an image repository, download the necessary data and finally view it in a locally installed DICOM viewer. Recent research activities in teleradiology [1, 2, 3, 4] focus on the implementation of ubiquitously accessible web-based DICOM viewers which simplify the access and the collaboration among radiologists. However, these solutions either have a weak performance, they run on the client side only, or they are not as feature rich as their desktop counterpart. In this contribution we present an architecture of a web based DICOM viewer which has both, good performance as well as advanced features such as the visualization of anatomical structures. On the client side only native web technologies are used. The whole architecture has been implemented and evaluated in the GoSmart environment, a planning tool for minimally invasive cancer treatment.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127967045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：