Innovation in Health Informatics: A Smart Healthcare Primer

422 Pages·2019·19.68 MB·English

by  Miltiadis D. Lytras (editor)

Innovation in Health Informatics
Innovation in Health Informatics
A Smart Healthcare Primer
Edited by
Miltiadis D. Lytras
Effat College of Engineering, Effat University, Jeddah, Saudi Arabia
Akila Sarirete
Effat College of Engineering, Effat University, Jeddah, Saudi Arabia
Series Editor
Miltiadis D. Lytras
Effat College of Engineering, Effat University, Jeddah, Saudi Arabia
Anna Visvizi
(cid:1)
Deree Cllege The American College of Greece, Greece;
Effat College of Business, Effat University, Jeddah, Saudi Arabia
Ernesto Damiani
University of Milan, Italy; Khalifa University, UAE
AcademicPressisanimprintofElsevier
125LondonWall,LondonEC2Y5AS,UnitedKingdom
525BStreet,Suite1650,SanDiego,CA92101,UnitedStates
50HampshireStreet,5thFloor,Cambridge,MA02139,UnitedStates
TheBoulevard,LangfordLane,Kidlington,OxfordOX51GB,UnitedKingdom
Copyright©2020ElsevierInc.Allrightsreserved.
Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,electronicor
mechanical,includingphotocopying,recording,oranyinformationstorageandretrievalsystem,without
permissioninwritingfromthepublisher.Detailsonhowtoseekpermission,furtherinformationaboutthe
Publisher’spermissionspoliciesandourarrangementswithorganizationssuchastheCopyrightClearance
CenterandtheCopyrightLicensingAgency,canbefoundatourwebsite:www.elsevier.com/permissions.
ThisbookandtheindividualcontributionscontainedinitareprotectedundercopyrightbythePublisher
(otherthanasmaybenotedherein).
Notices
Knowledgeandbestpracticeinthisfieldareconstantlychanging.Asnewresearchandexperiencebroadenour
understanding,changesinresearchmethods,professionalpractices,ormedicaltreatmentmaybecome
necessary.
Practitionersandresearchersmustalwaysrelyontheirownexperienceandknowledgeinevaluatingandusing
anyinformation,methods,compounds,orexperimentsdescribedherein.Inusingsuchinformationor
methodstheyshouldbemindfuloftheirownsafetyandthesafetyofothers,includingpartiesforwhomthey
haveaprofessionalresponsibility.
Tothefullestextentofthelaw,neitherthePublishernortheauthors,contributors,oreditors,assumeany
liabilityforanyinjuryand/ordamagetopersonsorpropertyasamatterofproductsliability,negligenceor
otherwise,orfromanyuseoroperationofanymethods,products,instructions,orideascontainedinthe
materialherein.
BritishLibraryCataloguing-in-PublicationData
AcataloguerecordforthisbookisavailablefromtheBritishLibrary
LibraryofCongressCataloging-in-PublicationData
AcatalogrecordforthisbookisavailablefromtheLibraryofCongress
ISBN:978-0-12-819043-2
ForInformationonallAcademicPresspublications
visitourwebsiteathttps://www.elsevier.com/books-and-journals
Publisher:StacyMasucci
SeniorAcquisitionEditor:RafaelE.Teixeira
EditorialProjectManager:SaraPianavilla
ProductionProjectManager:KiruthikaGovindaraju
CoverDesigner:GregHarris
TypesetbyMPSLimited,Chennai,India
Contents
List of contributors..............................................................................................xvii
Preface.................................................................................................................xxi
Acknowledgments................................................................................................xxv
Section A Smart Healthcare in the Era of Bid Data and Data Science...... 1
Chapter 1:Smart Healthcare: emerging technologies, best practices, and
sustainable policies................................................................................ 3
Miltiadis D. Lytras, Paraskevi Papadopoulou and Akila Sarirete
1.1 Introduction........................................................................................................3
1.2 Bridging innovative technologies and smart solutions in medicine and
healthcare............................................................................................................4
1.2.1 From genomics to proteomics to bioinformatics and health
informatics................................................................................................5
1.2.2 Ways of developing intelligent and personalized healthcare
interventions..............................................................................................7
1.2.3 Advancing medicine and healthcare: insights and wise solutions..............8
1.2.4 Ways of disseminating our healthcare experience.....................................8
1.3 Visioning the future of resilient Smart Healthcare.........................................10
1.4 Content management resilient Smart Healthcare systems cluster..................11
1.4.1 Resilient Smart Healthcare learning management systems cluster...........12
1.4.2 Resilient Smart Healthcare document management systems cluster........14
1.4.3 Resilient Smart Healthcare workflow automation...................................17
1.4.4 Resilient Smart Healthcare microcontent services and systems...............19
1.4.5 Resilient Smart Healthcare collaboration systems and services...............22
1.5 Networking technologies for resilient Smart Healthcare systems cluster......25
1.5.1 Smart systems.........................................................................................25
1.6 Data warehouses and distributed systems for resilient Smart Healthcare
applications.......................................................................................................26
v
vi Contents
1.6.1 Indicative smart applications for data warehouses in the context
of resilient Smart Healthcare design........................................................27
1.6.2 Smart systems.........................................................................................29
1.7 Analytics and business intelligence resilient Smart Healthcare systems
cluster...............................................................................................................30
1.7.1 Indicative smart applications...................................................................31
1.7.2 Smart systems.........................................................................................32
1.8 Emerging technologies resilient Smart Healthcare systems cluster...............32
1.8.1 Indicative smart applications...................................................................32
1.8.2 Smart systems.........................................................................................34
1.9 Resilient Smart Healthcare innovation............................................................34
1.9.1 The evolution of resilient smart..............................................................34
1.9.2 Indicative smart applications...................................................................35
1.10 Conclusion........................................................................................................36
References...................................................................................................................36
Further reading............................................................................................................37
Chapter 2:Syndromic surveillance using web data: a systematic review................... 39
Loukas Samaras, Elena Garcı´a-Barriocanal and Miguel-Angel Sicilia
2.1 Introduction: background and scope..................................................................39
2.2 Methodology: research protocol and stages......................................................41
2.2.1 Stage 1: Preparation, research questions, and queries...............................41
2.2.2 Stage 2: Data retrieval..............................................................................43
2.2.3 Stage 3: Data analysis: study selection and excluding criteria..................43
2.2.4 Stage 4: Data synthesis.............................................................................43
2.2.5 Stage 5: Results analysis...........................................................................44
2.2.6 Stage 6: Writing.......................................................................................44
2.3 Results and analysis...........................................................................................45
2.3.1 RQ1: Is the academic interest growing or declining?................................45
2.3.2 RQ2: Regarding syndromic surveillance using web data, what
aspects have been explored until today in the available literature?...........46
2.3.3 RQ3: What topics need further development and research?......................54
2.4 Discussion and conclusions................................................................................54
2.4.1 Results......................................................................................................54
2.4.2 Information systems and epidemics..........................................................55
2.4.3 Impact to society, ethics, and challenges..................................................57
2.4.4 Smart Healthcare innovations...................................................................58
2.4.5 Conclusions and outlook...........................................................................59
2.5 Teaching assignments........................................................................................61
Contents vii
Acknowledgments.......................................................................................................61
Author contributions...................................................................................................61
References...................................................................................................................61
Appendix: Included studies (alphabetical).................................................................63
Chapter 3:Natural Language Processing, Sentiment Analysis, and
Clinical Analytics................................................................................ 79
Adil Rajput
3.1 Introduction........................................................................................................79
3.1.1 Natural Language Processing and Healthcare/Clinical Analytics..............79
3.1.2 Sentiment analysis....................................................................................80
3.2 Natural Language Processing.............................................................................81
3.2.1 Traditional approach—key concepts.........................................................81
3.2.2 Statistical spproach—key concepts...........................................................86
3.3 Applications........................................................................................................91
3.3.1 Sentiment analysis....................................................................................91
3.3.2 Natural Language processing application in medical sciences..................92
3.4 Conclusion..........................................................................................................94
3.4.1 Future research directions.........................................................................94
3.4.2 Teaching assignments...............................................................................95
References...................................................................................................................95
Further reading............................................................................................................97
Section B Advanced Decision Making and Artificial Intelligence for
Smart Healthcare.......................................................................... 99
Chapter 4:Clinical decision support for infection control in surgical care................101
Marco Spruit and Sander van der Rijnst
4.1 Introduction......................................................................................................101
4.2 Research methodology.....................................................................................102
4.2.1 Data collection methods.........................................................................103
4.2.2 Design objectives....................................................................................104
4.3 Clinical decision support prototype.................................................................104
4.3.1 Contextual background...........................................................................105
4.3.2 Describing the surgical process using process-deliverable diagrams.......107
4.3.3 Data sources, data collection procedure, and data description.................109
4.3.4 Algorithms..............................................................................................109
viii Contents
4.3.5 Key performance indicators....................................................................111
4.3.6 Opportunities for local improvements.....................................................112
4.4 Exploratory data analysis.................................................................................112
4.4.1 Appropriate use of prophylactic antibiotics.............................................113
4.4.2 Maintenance of (perioperative) normothermia........................................113
4.4.3 Hygienic discipline in operating rooms regarding door movements........114
4.5 Discussion and implications.............................................................................117
4.5.1 Limitations and further research.............................................................118
4.6 Conclusion........................................................................................................119
4.7 Teaching assignments......................................................................................120
References.................................................................................................................120
Further reading..........................................................................................................121
Chapter 5:Human activity recognition using machine learning methods
in a smart healthcare environment......................................................123
Abdulhamit Subasi, Kholoud Khateeb, Tayeb Brahimi and Akila Sarirete
5.1 Introduction......................................................................................................123
5.2 Background and literature review....................................................................127
5.2.1 Human activity recognition with body sensors.......................................127
5.2.2 Human activity recognition with mobile phone sensors..........................129
5.3 Machine learning methods...............................................................................131
5.3.1 Artificial neural networks.....................................................................131
5.3.2 k-Nearest neighbor................................................................................131
5.3.3 Support vector machine........................................................................132
5.3.4 Na¨ıve Bayes.........................................................................................132
5.3.5 Classification and regression tree..........................................................132
5.3.6 C4.5 decision tree.................................................................................133
5.3.7 REPTree...............................................................................................133
5.3.8 LADTree algorithm..............................................................................133
5.3.9 Random tree classifiers.........................................................................134
5.3.10 Random forests.....................................................................................134
5.4 Results..............................................................................................................135
5.4.1 Experimental results for human activity recognition data taken
from body sensors..................................................................................136
5.4.2 Experimental results for human activity recognition data taken
from smartphone sensors........................................................................138
5.5 Discussion and conclusion...............................................................................140
5.6 Teaching assignments......................................................................................142
References.................................................................................................................142
Contents ix
Chapter 6:Application of machine learning and image processing for detection
of breast cancer.................................................................................145
Muhammad Kashif, Kaleem Razzaq Malik, Sohail Jabbar
and Junaid Chaudhry
6.1 Introduction......................................................................................................145
6.1.1 Mammograms.........................................................................................146
6.1.2 Preprocessing..........................................................................................147
6.1.3 Segmentation..........................................................................................147
6.1.4 Machine learning....................................................................................147
6.2 Literature review..............................................................................................149
6.3 Proposed work..................................................................................................150
6.3.1 Dataset....................................................................................................150
6.3.2 Noise removal (preprocessing)................................................................150
6.3.3 Segmentation process.............................................................................152
6.3.4 Feature extraction...................................................................................153
6.3.5 Training model and testing.....................................................................155
6.3.6 Classification..........................................................................................155
6.3.7 Performance evaluation metrics..............................................................155
6.3.8 f-Score measure......................................................................................156
6.4 Results..............................................................................................................157
6.5 Discussions.......................................................................................................158
6.6 Conclusion........................................................................................................160
6.7 Research contribution highlights.....................................................................161
6.8 Teaching assignments......................................................................................161
References.................................................................................................................162
Chapter 7: Toward information preservation in healthcare systems........................163
Omar El Zarif and Ramzi A. Haraty
7.1 Introduction......................................................................................................163
7.2 The literature review........................................................................................165
7.2.1 Log files.................................................................................................165
7.2.2 Graph......................................................................................................166
7.2.3 Clustering...............................................................................................167
7.2.4 Matrices..................................................................................................167
7.3 Our approach....................................................................................................168
7.3.1 Background............................................................................................169
7.3.2 Adaptation to multilevel.........................................................................170
7.3.3 Complexity analysis................................................................................177
x Contents
7.4 Experimental results.........................................................................................177
7.4.1 Performance results of the detection algorithm.......................................178
7.4.2 Performance results of the recovery algorithm........................................180
7.4.3 Memory footprint analysis......................................................................182
7.5 Conclusion........................................................................................................183
7.6 Teaching assignments......................................................................................184
References.................................................................................................................184
Section C Emerging technologies and systems for smart
healthcare......................................................................................187
Chapter 8:Security and privacy solutions for smart healthcare systems .................189
Yang Lu and Richard O. Sinnott
8.1 Introduction......................................................................................................189
8.2 Smart healthcare framework and techniques...................................................191
8.3 Identified issues and solutions.........................................................................196
8.3.1 Authentication........................................................................................198
8.3.2 Privacy-aware access control..................................................................202
8.3.3 Anonymization.......................................................................................206
8.4 Discussion.........................................................................................................210
8.5 Conclusions and open research issues in future..............................................211
8.6 Teaching assignments......................................................................................212
References.................................................................................................................212
Further reading..........................................................................................................216
Chapter 9:Cloud-based health monitoring framework using smart sensors
and smartphone.................................................................................217
Abdulhamit Subasi, Lejla Bandic and Saeed Mian Qaisar
9.1 Introduction......................................................................................................217
9.2 Background and literature review....................................................................220
9.2.1 Electrocardiogram in cloud-based mobile healthcare..............................221
9.2.2 Electroencephalogram in cloud-based mobile healthcare........................223
9.3 Signal acquisition, segmentation, and denoising methods..............................225
9.3.1 Adaptive rate acquisition........................................................................226
9.3.2 Adaptive rate segmentation.....................................................................226
9.3.3 Adaptive rate interpolation.....................................................................227
9.3.4 Adaptive rate filtering.............................................................................227