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A Yes/No Answer Generator Based on Sentiment-Word Scores in Biomedical Question Answering 生物医学问答中基于情感词得分的是/否答案生成器
Data Analytics in Medicine Pub Date : 2017-07-01 DOI: 10.4018/978-1-7998-1204-3.ch005
SarroutiMourad, El AlaouiSaid Ouatik
{"title":"A Yes/No Answer Generator Based on Sentiment-Word Scores in Biomedical Question Answering","authors":"SarroutiMourad, El AlaouiSaid Ouatik","doi":"10.4018/978-1-7998-1204-3.ch005","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.ch005","url":null,"abstract":"Background and Objective: Yes/no question answering (QA) in open-domain is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in the biomedical domain. Yes/no QA aims at answering yes/no questions, which are seeking for a clear “yes” or “no” answer. In this paper, we present a novel yes/no answer generator based on sentiment-word scores in biomedical QA. Methods: In the proposed method, we first use the Stanford CoreNLP for tokenization and part-of-speech tagging all relevant passages to a given yes/no question. We then assign a sentiment score based on SentiWordNet to each word of the passages. Finally, the decision on either the answers “yes” or “no” is based on the obtained sentiment-passages score: “yes” for a positive final sentiment-passages score and “no” for a negative one. Results: Experimental evaluations performed on BioASQ collections show that the proposed method is more effective as compared with the current state-of-the-art method, and significantly outperforms it by an average of 15.68% in terms of accuracy.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125190600","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}
引用次数: 1
Integrated Approach for Automatic Crackle Detection Based on Fractal Dimension and Box Filtering 基于分形维数和盒滤波的裂纹自动检测集成方法
Data Analytics in Medicine Pub Date : 2016-10-01 DOI: 10.4018/IJRQEH.2016100103
Cátia M. R. Pinho, Ana Oliveira, C. Jácome, João Rodrigues, A. Marques
{"title":"Integrated Approach for Automatic Crackle Detection Based on Fractal Dimension and Box Filtering","authors":"Cátia M. R. Pinho, Ana Oliveira, C. Jácome, João Rodrigues, A. Marques","doi":"10.4018/IJRQEH.2016100103","DOIUrl":"https://doi.org/10.4018/IJRQEH.2016100103","url":null,"abstract":"Crackles are adventitious respiratory sounds (RS) that provide valuable information on different respiratory conditions. Nevertheless, crackles automatic detection in RS is challenging, mainly when collected in clinical settings. This study aimed to develop an algorithm for automatic crackle detection/characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on 4 main procedures: i) recognition of a potential crackle; ii) verification of its validity; iii) characterisation of crackles parameters; and iv) optimisation of the algorithm parameters. Twenty-four RS files acquired in clinical settings were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with a multi-annotator gold standard agreement. High level of overall performance (F-score=92%) was achieved. The results highlight the potential of the algorithm for automatic crackle detection and characterisation of RS acquired in clinical settings.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115516315","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}
引用次数: 14
Information Security Standards in Healthcare Activities 医疗保健活动中的信息安全标准
Data Analytics in Medicine Pub Date : 2016-10-01 DOI: 10.4018/IJRQEH.2016100102
José Gaivéo
{"title":"Information Security Standards in Healthcare Activities","authors":"José Gaivéo","doi":"10.4018/IJRQEH.2016100102","DOIUrl":"https://doi.org/10.4018/IJRQEH.2016100102","url":null,"abstract":"Information is mandatory in healthcare activities and in all that are related to it. In this same sense, people that deal with those information requires attention because patient´s information could be exposed. The use of directions stated by information security standards might allow a proactive attitude in the face of the diversity of threats that as the potential to explore the vulnerabilities of organizational assets. This article intends to recognize information threats and vulnerabilities that could be explored, using information security international standards to support the activities needed to assume information safeguard. Another intention is the establishment of a basis of references in information security to define a level of risk classification to build a referential to the potential that a given threat has to exploit the vulnerabilities of informational assets, preventing damages to personal and organizational property, and also activity continuity, assuming information as the main resource.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133122690","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}
引用次数: 1
Human-Data Interaction in Healthcare 医疗保健中的人机交互
Data Analytics in Medicine Pub Date : 2016-02-18 DOI: 10.4018/978-1-7998-1204-3.CH058
F. Cabitza, A. Locoro
{"title":"Human-Data Interaction in Healthcare","authors":"F. Cabitza, A. Locoro","doi":"10.4018/978-1-7998-1204-3.CH058","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.CH058","url":null,"abstract":"In this chapter, we focus on an emerging strand of IT-oriented research, namely Human-Data Interaction (HDI) and on how this can be applied to healthcare. HDI regards both how humans create and use data by means of interactive systems, which can both assist and constrain them and the operational level of data work, which is both work on data and by data. Healthcare is a challenging arena where to test the potential of HDI towards a new, user-centered perspective on how to support and assess “data work”. This is especially true in current times where data are becoming increasingly big and many tools are available for the lay people, including doctors and nurses, to interact with health-related data. This chapter is a contribution in the direction of considering health-related data through the lens of HDI, and of framing data visualization tools in this strand of research. The intended aim is to let the subtler peculiarities among different kind of data and of their use emerge and be addressed adequately. Our point is that doing so can promote the design of more usable tools that can support data work from a user-centered and data quality perspective and the evidence-based validation of these tools.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114693772","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}
引用次数: 8
Integral Equation Formulations and Related Numerical Solution Methods in Some Biomedical Applications of Electromagnetic Fields 电磁场在某些生物医学应用中的积分方程及相关数值求解方法
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1204-3.ch013
D. Poljak, M. Cvetković, V. Doric, I. Zulim, Zoran Đogaš, M. Vidaković, J. Haueisen, K. Drissi
{"title":"Integral Equation Formulations and Related Numerical Solution Methods in Some Biomedical Applications of Electromagnetic Fields","authors":"D. Poljak, M. Cvetković, V. Doric, I. Zulim, Zoran Đogaš, M. Vidaković, J. Haueisen, K. Drissi","doi":"10.4018/978-1-7998-1204-3.ch013","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.ch013","url":null,"abstract":"The paper reviews certain integral equation approaches and related numerical methods used in studies of biomedical applications of electromagnetic fields pertaining to transcranial magnetic stimulation (TMS) and nerve fiber stimulation. TMS is analyzed by solving the set of coupled surface integral equations (SIEs), while the numerical solution of governing equations is carried out via Method of Moments (MoM) scheme. A myelinated nerve fiber, stimulated by a current source, is represented by a straight thin wire antenna. The model is based on the corresponding homogeneous Pocklington integro-differential equation solved by means of the Galerkin Bubnov Indirect Boundary Element Method (GB-IBEM). Some illustrative numerical results for the TMS induced fields and intracellular current distribution along the myelinated nerve fiber (active and passive), respectively, are presented in the paper.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129591225","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}
引用次数: 0
Energy Efficient Particle Optimized Compressed ECG Data over Zigbee Environment 节能粒子优化压缩心电图数据在Zigbee环境
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-0660-7.CH014
Dilip Kumar, Rajeev Kumar, Tony Singla
{"title":"Energy Efficient Particle Optimized Compressed ECG Data over Zigbee Environment","authors":"Dilip Kumar, Rajeev Kumar, Tony Singla","doi":"10.4018/978-1-5225-0660-7.CH014","DOIUrl":"https://doi.org/10.4018/978-1-5225-0660-7.CH014","url":null,"abstract":"Standard Electrocardiogram Tracking instruments are huge to carry away over the remote areas for the surveillance. Holter is the compact instrument meant for collecting ECG of a patient without a pause while the patient is on the go of their daily activities. Holter works on battery for 48 hours without any angle of transmission but when allowed to transmit battery power dies soon, for these purposes some energy saving techniques is required. In this chapter the authors have proposed a Wavelet based Compression Technique, followed by Optimization under Genetic Algorithm and Particle Swarm Optimization. Compressed and Optimized ECG data has been transferred over Zigbee IEEE 802.15.4 with the intention of saving energy implicating it on a hardware chip. Transferred data will be available to the Doctor for on time treatment and further examination and storage. Embedded prior techniques in Holter can enhance its life, with fact of sending crucial data.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116506046","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}
引用次数: 1
Bidirectional Spreading Activation Method for Finding Human Diseases Relatedness Using Well-Formed Disease Ontology 基于格式良好的疾病本体的人类疾病相关性的双向传播激活方法
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/IJCCP.2017010104
S. Fathalla, Yaman Kannot
{"title":"Bidirectional Spreading Activation Method for Finding Human Diseases Relatedness Using Well-Formed Disease Ontology","authors":"S. Fathalla, Yaman Kannot","doi":"10.4018/IJCCP.2017010104","DOIUrl":"https://doi.org/10.4018/IJCCP.2017010104","url":null,"abstract":"The successful application of semantic web in medical informatics and the fast expanding of biomedical knowledge have prompted to the requirement for a standardized representation of knowledge and an efficient algorithm for querying this extensive information. Spreading activation algorithm is suitable to work on incomplete and large datasets. This article presents a method called SAOO (Spreading Activation over Ontology) which identifies the relatedness between two human diseases by applying spreading activation algorithm based on bidirectional search technique over large disease ontology. The proposed methodology is divided into two phases: Semantic matching and Disease relatedness detection. In Semantic Matching, semantically identify diseases in user's query in the ontology. In the Disease Relatedness Detection, URIs of the diseases are passed to the relatedness detector which returns the set of diseases that may connect them. The proposed method improves the non-semantic medical systems by considering semantic domain knowledge to infer diseases relatedness.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132274639","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}
引用次数: 2
Detecting Human Diseases Relatedness 人类疾病相关性检测
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1204-3.ch026
S. Fathalla
{"title":"Detecting Human Diseases Relatedness","authors":"S. Fathalla","doi":"10.4018/978-1-7998-1204-3.ch026","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.ch026","url":null,"abstract":"Due to the ubiquitous availability of the information on the web, there is a great need for a standardized representation of this information. Therefore, developing an efficient algorithm for retrieving information from knowledge graphs is a key challenge for many semantic web applications. This article presents spreading activation over ontology (SAOO) approach in order to detect the relatedness between two human diseases by applying spreading activation algorithm based on bidirectional search technique. The proposed approach detects two diseases relatedness by considering semantic domain knowledge. The methodology of the proposed work is divided into two phases: Semantic Matching and Diseases Relatedness Detection. In semantic matching, diseases within the user-submitted query are semantically identified in the ontology graph. In diseases relatedness detection, the relatedness between the two diseases is detected by using bidirectional-based spreading activation on the ontology graph. The classification of these diseases is provided as well.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129601405","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}
引用次数: 0
Modelling and Simulating Complex Systems in Biology 生物学中复杂系统的建模和模拟
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1204-3.ch048
P. Ballet, Jérémy Rivière, Alain Pothet, M. Theron, K. Pichavant, F. Abautret, Alexandra Fronville, V. Rodin
{"title":"Modelling and Simulating Complex Systems in Biology","authors":"P. Ballet, Jérémy Rivière, Alain Pothet, M. Theron, K. Pichavant, F. Abautret, Alexandra Fronville, V. Rodin","doi":"10.4018/978-1-7998-1204-3.ch048","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.ch048","url":null,"abstract":"Modelling and teaching complex biological systems is a difficult process. Multi-Agent Based Simulations (MABS) have proved to be an appropriate approach both in research and education when dealing with such systems including emergent, self-organizing phenomena. This chapter presents NetBioDyn, an original software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular systems. Thanks to its specific graphical user interface guided by the multi-agent paradigm, this software does not need any prerequisite in computer programming. It thus allows users to create in a simple way bottom-up models where unexpected behaviours can emerge from many interacting entities. This multi-platform software has been used in middle schools, high schools and universities since 2010. A qualitative survey is also presented, showing its ability to adapt to a wide and heterogeneous audience. The Java executable and the source code are available online at http://virtulab.univ-brest.fr.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125912399","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}
引用次数: 0
Ensuring Privacy of Participants Recruited via Social Media 确保通过社交媒体招募参与者的隐私
Data Analytics in Medicine Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1204-3.ch077
C. Unnithan, P. Swatman, J. Kelder
{"title":"Ensuring Privacy of Participants Recruited via Social Media","authors":"C. Unnithan, P. Swatman, J. Kelder","doi":"10.4018/978-1-7998-1204-3.ch077","DOIUrl":"https://doi.org/10.4018/978-1-7998-1204-3.ch077","url":null,"abstract":"Researchers worldwide are increasingly looking to recruit research participants via social media (particularly @Facebook and @Twitter) because they appear to offer access to a wider range of research participants and afford inherently convenient tools for recruitment. In Australia, the National Statement on Ethical Conduct in Human Research, together with the federal Privacy law and a number of state-based privacy statutes, provide support and guidance for this novel approach. This article offers a preliminary analysis and discussion of this trend from an Australian perspective, illustrated by an enquiry into the ethical challenges posed by social media-based recruitment, conducted in an Australian university in 2015. Leximancer™ was used as an analytical tool and the content from social media sites used for a small number of research studies conducted up to 2015, taken in conjunction with the various national human research ethics guidelines, offered a means of understanding how ethical challenges of privacy and anonymity can be addressed for responsible social media-based research.","PeriodicalId":177246,"journal":{"name":"Data Analytics in Medicine","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130128258","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}
引用次数: 0
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