Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001829
Htoo Aung Maw, Hannan Xiao, B. Christianson, J. Malcolm
Wireless Sensor Networks (WSNs) have recently attracted a lot of attention in the research community because it is easy to deploy them in the physical environment and collect and disseminate environmental data from them. The collected data from sensor nodes can vary based on what kind of application is used for WSNs. Data confidentiality and access control to that collected data are the most challenging issues in WSNs because the users are able to access data from the different location via ad-hoc manner. Access control is one of the critical requirements to prevent unauthorised access from users. The current access control models in information systems cannot be applied straightforwardly because of some limitations namely limited energy, resource and memory, and low computation capability. Based on the requirements of WSNs, we proposed the Break-The-Glass Access Control (BTG-AC) model which is the modified and redesigned version of Break-The-Glass Role-Based Access Control (BTG-RBAC) model. The several changes within the access control engine are made in BTG-RBAC to apply and fit in WSNs. We developed the BTG-AC model in Ponder2 package. Also a medical scenario was developed to evaluate the BTG-AC model for medical data in WSNs. In this paper, detail design, implementation phase, evaluation result and policies evaluation for the BTG-AC model are presented. Based on the evaluation result, the BTG-AC model can be used in WSNs after several modifications have been made under Ponder2 Package.
{"title":"An evaluation of break-the-glass access control model for medical data in wireless sensor networks","authors":"Htoo Aung Maw, Hannan Xiao, B. Christianson, J. Malcolm","doi":"10.1109/HealthCom.2014.7001829","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001829","url":null,"abstract":"Wireless Sensor Networks (WSNs) have recently attracted a lot of attention in the research community because it is easy to deploy them in the physical environment and collect and disseminate environmental data from them. The collected data from sensor nodes can vary based on what kind of application is used for WSNs. Data confidentiality and access control to that collected data are the most challenging issues in WSNs because the users are able to access data from the different location via ad-hoc manner. Access control is one of the critical requirements to prevent unauthorised access from users. The current access control models in information systems cannot be applied straightforwardly because of some limitations namely limited energy, resource and memory, and low computation capability. Based on the requirements of WSNs, we proposed the Break-The-Glass Access Control (BTG-AC) model which is the modified and redesigned version of Break-The-Glass Role-Based Access Control (BTG-RBAC) model. The several changes within the access control engine are made in BTG-RBAC to apply and fit in WSNs. We developed the BTG-AC model in Ponder2 package. Also a medical scenario was developed to evaluate the BTG-AC model for medical data in WSNs. In this paper, detail design, implementation phase, evaluation result and policies evaluation for the BTG-AC model are presented. Based on the evaluation result, the BTG-AC model can be used in WSNs after several modifications have been made under Ponder2 Package.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115061152","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001883
Medina Hadjem, Osman Salem, Farid Naït-Abdesselam
Cardiovascular diseases (CVD) are known to be the most widespread causes to death. Therefore, detecting earlier signs of cardiac anomalies is of prominent importance to ease the treatment of any cardiac complication or take appropriate actions. Electrocardiogram (ECG) is used by doctors as an important diagnosis tool and in most cases, it's recorded and analyzed at hospital after the appearance of first symptoms or recorded by patients using a device named holter ECG and analyzed afterward by doctors. In fact, there is a lack of systems able to capture ECG and analyze it remotely before the onset of severe symptoms. With the development of wearable sensor devices having wireless transmission capabilities, there is a need to develop real time systems able to accurately analyze ECG and detect cardiac abnormalities. In this paper, we propose a new CVD detection system using Wireless Body Area Networks (WBAN) technology. This system processes the captured ECG using filtering and Undecimated Wavelet Transform (UWT) techniques to remove noises and extract nine main ECG diagnosis parameters, then the system uses a Bayesian Network Classifier model to classify ECG based on its parameters into four different classes: Normal, Premature Atrial Contraction (PAC), Premature Ventricular Contraction (PVC) and Myocardial Infarction (MI). The experimental results on ECGs from real patients databases show that the average detection rate (TPR) is 96.1% for an average false alarm rate (FPR) of 1.3%.
{"title":"An ECG monitoring system for prediction of cardiac anomalies using WBAN","authors":"Medina Hadjem, Osman Salem, Farid Naït-Abdesselam","doi":"10.1109/HealthCom.2014.7001883","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001883","url":null,"abstract":"Cardiovascular diseases (CVD) are known to be the most widespread causes to death. Therefore, detecting earlier signs of cardiac anomalies is of prominent importance to ease the treatment of any cardiac complication or take appropriate actions. Electrocardiogram (ECG) is used by doctors as an important diagnosis tool and in most cases, it's recorded and analyzed at hospital after the appearance of first symptoms or recorded by patients using a device named holter ECG and analyzed afterward by doctors. In fact, there is a lack of systems able to capture ECG and analyze it remotely before the onset of severe symptoms. With the development of wearable sensor devices having wireless transmission capabilities, there is a need to develop real time systems able to accurately analyze ECG and detect cardiac abnormalities. In this paper, we propose a new CVD detection system using Wireless Body Area Networks (WBAN) technology. This system processes the captured ECG using filtering and Undecimated Wavelet Transform (UWT) techniques to remove noises and extract nine main ECG diagnosis parameters, then the system uses a Bayesian Network Classifier model to classify ECG based on its parameters into four different classes: Normal, Premature Atrial Contraction (PAC), Premature Ventricular Contraction (PVC) and Myocardial Infarction (MI). The experimental results on ECGs from real patients databases show that the average detection rate (TPR) is 96.1% for an average false alarm rate (FPR) of 1.3%.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130631721","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 : 2014-10-01DOI: 10.1109/HEALTHCOM.2014.7001868
Thiago Fernandes de Freitas Dias, Domingos Alves, J. C. Felipe
The translation or mapping between terminologies in healthcare is one of the ways to achieve semantic interoperability between information systems. Accordingly, we propose a method to assist the translation of terminologies based on the association rules mining in integrated databases containing data encoded with two different terminologies. This method also uses text search (string matching) between terms. The extracted rules proved the correct translation of some terms and when a valid rule could not be extracted, textual search proved to be a good resource. Further work will be undertaken to quantify the efficiency of the method through expert analysis.
{"title":"Method for the mapping between health terminologies aiming systems interoperability","authors":"Thiago Fernandes de Freitas Dias, Domingos Alves, J. C. Felipe","doi":"10.1109/HEALTHCOM.2014.7001868","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2014.7001868","url":null,"abstract":"The translation or mapping between terminologies in healthcare is one of the ways to achieve semantic interoperability between information systems. Accordingly, we propose a method to assist the translation of terminologies based on the association rules mining in integrated databases containing data encoded with two different terminologies. This method also uses text search (string matching) between terms. The extracted rules proved the correct translation of some terms and when a valid rule could not be extracted, textual search proved to be a good resource. Further work will be undertaken to quantify the efficiency of the method through expert analysis.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128587486","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001835
Yi Liu, Chonho Lee, Bu-Sung Lee, James K. R. Stevenson, M. McKeown
Recent studies have suggested significant differences in motor performances of Parkinson's Disease (PD) patients who have L-dopa induced dyskinesias (LIDs), even when off of L-dopa medication. The pathophysiology of LIDs remains obscure, so applying data-mining techniques to the patients' motor performance may provide some heuristic insight. This paper investigated visually-guided tracking performance of PD patients using data mining techniques to reveal the differences between dyskinesia and non-dyskinesia patients. We found that K-means clustering of the root mean square (RMS) tracking error at faster tracking speeds and with ambiguous visual stimuli was able to effectively discriminate between the two groups with 77.8% accuracy. Decision tree classification was less accurate (68.4%) and determined that years since diagnosis was the best feature to distinguish between groups. Our results suggest that data mining methodologies may provide novel insights into features of the neurovegetative disease.
{"title":"Analysis of visually guided tracking performance in Parkinson's disease","authors":"Yi Liu, Chonho Lee, Bu-Sung Lee, James K. R. Stevenson, M. McKeown","doi":"10.1109/HealthCom.2014.7001835","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001835","url":null,"abstract":"Recent studies have suggested significant differences in motor performances of Parkinson's Disease (PD) patients who have L-dopa induced dyskinesias (LIDs), even when off of L-dopa medication. The pathophysiology of LIDs remains obscure, so applying data-mining techniques to the patients' motor performance may provide some heuristic insight. This paper investigated visually-guided tracking performance of PD patients using data mining techniques to reveal the differences between dyskinesia and non-dyskinesia patients. We found that K-means clustering of the root mean square (RMS) tracking error at faster tracking speeds and with ambiguous visual stimuli was able to effectively discriminate between the two groups with 77.8% accuracy. Decision tree classification was less accurate (68.4%) and determined that years since diagnosis was the best feature to distinguish between groups. Our results suggest that data mining methodologies may provide novel insights into features of the neurovegetative disease.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132505615","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001806
K. Chelette, Cheryl Carrico, L. Nichols, Emily Salyers, L. Sawaki
Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that can modulate neuroplasticity (the capacity for brain reorganization). Neuroplastic change correlates with upper extremity (UE) recovery after brain lesions. Different electrode configurations of tDCS paired with UE motor training can have different effects in distinct populations. We are conducting the first randomized, double-blind, placebo-controlled trial to investigate which tDCS configuration may best enhance outcomes of UE motor training for stroke survivors with chronic, severe hemiparesis (i.e., little or no wrist or hand movement). We have assigned subjects to 1 of 4 groups: 1) “Anodal”: anodal tDCS to excite ipsilesional motor cortex; 2) “Cathodal”: cathodal tDCS to inhibit contralesional motor cortex; 3) “Dual”: a simultaneous combination of anodal and cathodal tDCS; or 4) “Sham” tDCS. Intervention (10 sessions) consists of tDCS followed by 3 hours of intensive, task-oriented UE training in each session. Our primary outcome measure is Fugl-Meyer Assessment. Our secondary outcome measures are Action Research Arm Test and Stroke Impact Scale. We have conducted evaluations at baseline and post-intervention. Preliminary results from 26 of (projected) 44 subjects indicate substantially greater improvement for the “Cathodal” group than other groups. These findings differ from evidence about tDCS in rehabilitation of mild-to-moderate hemiparesis. Completion of our study will include full analysis of neuroplastic change associated with intervention.
{"title":"Effects of electrode configurations in transcranial direct current stimulation after stroke","authors":"K. Chelette, Cheryl Carrico, L. Nichols, Emily Salyers, L. Sawaki","doi":"10.1109/HealthCom.2014.7001806","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001806","url":null,"abstract":"Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that can modulate neuroplasticity (the capacity for brain reorganization). Neuroplastic change correlates with upper extremity (UE) recovery after brain lesions. Different electrode configurations of tDCS paired with UE motor training can have different effects in distinct populations. We are conducting the first randomized, double-blind, placebo-controlled trial to investigate which tDCS configuration may best enhance outcomes of UE motor training for stroke survivors with chronic, severe hemiparesis (i.e., little or no wrist or hand movement). We have assigned subjects to 1 of 4 groups: 1) “Anodal”: anodal tDCS to excite ipsilesional motor cortex; 2) “Cathodal”: cathodal tDCS to inhibit contralesional motor cortex; 3) “Dual”: a simultaneous combination of anodal and cathodal tDCS; or 4) “Sham” tDCS. Intervention (10 sessions) consists of tDCS followed by 3 hours of intensive, task-oriented UE training in each session. Our primary outcome measure is Fugl-Meyer Assessment. Our secondary outcome measures are Action Research Arm Test and Stroke Impact Scale. We have conducted evaluations at baseline and post-intervention. Preliminary results from 26 of (projected) 44 subjects indicate substantially greater improvement for the “Cathodal” group than other groups. These findings differ from evidence about tDCS in rehabilitation of mild-to-moderate hemiparesis. Completion of our study will include full analysis of neuroplastic change associated with intervention.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126359540","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001886
S. Hara, T. Tsujioka, Takunori Shimazaki, Kouhei Tezuka, Masayuki Ichikawa, Masato Ariga, Hajime Nakamura, Takashi Kawabata, Kenji Watanabe, M. Ise, Noa Arime, H. Okuhata
We have developed a real-time vital signs monitoring system for two years in 2012 and 2013. Just by putting a single vital sensor node to the back waist position of each player and placing four data collection nodes around a field, the system can monitor at a note PC heart rate (HR), energy expenditure (EE) and body temperature (BT) for all players during a football game in real-time, periodically and reliably. The system is based on novel vital sensing technique and wireless data transmission technique. This paper introduces the two techniques in the system, presents some problems encountered in the system development and discusses solutions for them.
{"title":"Elements of a real-time vital signs monitoring system for players during a football game","authors":"S. Hara, T. Tsujioka, Takunori Shimazaki, Kouhei Tezuka, Masayuki Ichikawa, Masato Ariga, Hajime Nakamura, Takashi Kawabata, Kenji Watanabe, M. Ise, Noa Arime, H. Okuhata","doi":"10.1109/HealthCom.2014.7001886","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001886","url":null,"abstract":"We have developed a real-time vital signs monitoring system for two years in 2012 and 2013. Just by putting a single vital sensor node to the back waist position of each player and placing four data collection nodes around a field, the system can monitor at a note PC heart rate (HR), energy expenditure (EE) and body temperature (BT) for all players during a football game in real-time, periodically and reliably. The system is based on novel vital sensing technique and wireless data transmission technique. This paper introduces the two techniques in the system, presents some problems encountered in the system development and discusses solutions for them.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134362465","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 : 2014-10-01DOI: 10.1109/HEALTHCOM.2014.7001823
Isaac Golden, A. Stranieri, T. Sahama, S. Pilapitiya, Sisira Siribaddana, Stephen Vaughan
Culturally, philosophically and religiously diverse medical systems including Western medicine, Traditional Chinese Medicine, Ayurvedic Medicine and Homeopathic Medicine, once situated in places and times relatively unconnected from each other, currently co-exist to a point where patients must choose which system to consult. These decisions require comparative analyses, yet the divergence in key underpinning assumptions is so great that comparisons cannot easily be made. However, diverse medical systems can be meaningfully juxtaposed for the purpose of making practical decisions if relevant information is presented appropriately. Information regarding privacy provisions inherent in the typical practice of each medical system is an important element in this juxtaposition. In this paper the information needs of patients making decisions regarding the selection of a medical system, are examined.
{"title":"Informatics to support patient choice between diverse medical systems","authors":"Isaac Golden, A. Stranieri, T. Sahama, S. Pilapitiya, Sisira Siribaddana, Stephen Vaughan","doi":"10.1109/HEALTHCOM.2014.7001823","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2014.7001823","url":null,"abstract":"Culturally, philosophically and religiously diverse medical systems including Western medicine, Traditional Chinese Medicine, Ayurvedic Medicine and Homeopathic Medicine, once situated in places and times relatively unconnected from each other, currently co-exist to a point where patients must choose which system to consult. These decisions require comparative analyses, yet the divergence in key underpinning assumptions is so great that comparisons cannot easily be made. However, diverse medical systems can be meaningfully juxtaposed for the purpose of making practical decisions if relevant information is presented appropriately. Information regarding privacy provisions inherent in the typical practice of each medical system is an important element in this juxtaposition. In this paper the information needs of patients making decisions regarding the selection of a medical system, are examined.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131619051","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001896
Yi Chai, Guixia Kang, Ningbo Zhang, Jianwei Wu, Xiaoshuang Liu, Yuncheng Liu
Chronic diseases are gradually becoming the principal factors of harm to people's health. Fortunately, the development of e-health provides a novel thought for chronic disease prevention and treatment. This paper focuses on the research of cardiovascular disease (CVDs) prevention and early warning techniques using e-health and data mining. In this paper, we will use weighted associative classification algorithm to model the data in healthcare database to determine the level of cardiovascular risk. Besides, on the basis of data mining and knowledge discovery, intelligent warning mechanisms are proposed to provide different services to patients with different levels of risk. The experimental results show that the used classification algorithm is a more effective mining algorithm in the field of healthcare with higher accuracy and better comprehension. Our study is of definite significance to help control risk level of CVDs patients.
{"title":"Research on CVDs prediction and early warning techniques in healthcare monitoring system","authors":"Yi Chai, Guixia Kang, Ningbo Zhang, Jianwei Wu, Xiaoshuang Liu, Yuncheng Liu","doi":"10.1109/HealthCom.2014.7001896","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001896","url":null,"abstract":"Chronic diseases are gradually becoming the principal factors of harm to people's health. Fortunately, the development of e-health provides a novel thought for chronic disease prevention and treatment. This paper focuses on the research of cardiovascular disease (CVDs) prevention and early warning techniques using e-health and data mining. In this paper, we will use weighted associative classification algorithm to model the data in healthcare database to determine the level of cardiovascular risk. Besides, on the basis of data mining and knowledge discovery, intelligent warning mechanisms are proposed to provide different services to patients with different levels of risk. The experimental results show that the used classification algorithm is a more effective mining algorithm in the field of healthcare with higher accuracy and better comprehension. Our study is of definite significance to help control risk level of CVDs patients.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121260434","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001869
L. Minelli, M. C. d'Ornellas, Ana T. Winck
The gradual increase of cancer cases worldwide has been posing a need on the use of computing resources to accurately retrieve the information recorded in databases. One can highlight the retrieved information importance from a specialist in order to better evaluate pathological response and predict the cancer patient prognosis. This paper presents a way to represent knowledge of cancer registries with emphasis on prognosis. It makes use data mining techniques to find patterns in data stored for patient's lifetime in similar situations. The work is focused on the generation of association rules to find patterns on these registries in order to measure the patient prognosis and drive healthcare experts conclusions. A validation against international oncology organizations and health publications was also made to ensure data and work reliability.
{"title":"Knowledge representation for lung cancer patients' prognosis","authors":"L. Minelli, M. C. d'Ornellas, Ana T. Winck","doi":"10.1109/HealthCom.2014.7001869","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001869","url":null,"abstract":"The gradual increase of cancer cases worldwide has been posing a need on the use of computing resources to accurately retrieve the information recorded in databases. One can highlight the retrieved information importance from a specialist in order to better evaluate pathological response and predict the cancer patient prognosis. This paper presents a way to represent knowledge of cancer registries with emphasis on prognosis. It makes use data mining techniques to find patterns in data stored for patient's lifetime in similar situations. The work is focused on the generation of association rules to find patterns on these registries in order to measure the patient prognosis and drive healthcare experts conclusions. A validation against international oncology organizations and health publications was also made to ensure data and work reliability.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126896377","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001900
Isela Macia
The variety of Electronic Health Records (EHRs) makes interoperability a global trend in healthcare, which is of a paramount interest to the Brazilian Ministry of Health. In particular, semantic interoperability receives a special attention since it ensures that different health information systems make the same interpretation of the exchanged information. Although several standards have been documented to support interoperability (e.g. HL7 and IHE), achieving the semantic one is still a challenge. In this context, this paper represents a step towards supporting seamless semantic interoperability by combining different health standards (OpenEHR, IHE and HL7). It describes a software architecture that illustrates the role of different health standards in a semantic interoperability environment. Moreover, it introduces a process aiming at supporting the sematic validation of clinical documents. Finally, it documents several findings, such as benefits of the combined use of OpenEHR and IHE profiles.
{"title":"Towards a semantic interoperability environment","authors":"Isela Macia","doi":"10.1109/HealthCom.2014.7001900","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001900","url":null,"abstract":"The variety of Electronic Health Records (EHRs) makes interoperability a global trend in healthcare, which is of a paramount interest to the Brazilian Ministry of Health. In particular, semantic interoperability receives a special attention since it ensures that different health information systems make the same interpretation of the exchanged information. Although several standards have been documented to support interoperability (e.g. HL7 and IHE), achieving the semantic one is still a challenge. In this context, this paper represents a step towards supporting seamless semantic interoperability by combining different health standards (OpenEHR, IHE and HL7). It describes a software architecture that illustrates the role of different health standards in a semantic interoperability environment. Moreover, it introduces a process aiming at supporting the sematic validation of clinical documents. Finally, it documents several findings, such as benefits of the combined use of OpenEHR and IHE profiles.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126371014","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}
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