@incollection{, 1CC770137BF16537AFF9493D9CBF53E6 , author={{Md.Asadullah} and {MamunarRashid} and {PriyankaBosu} and {EmonAhmed} and {SabehaTamanna} and {Bangabandhu Sheikh Mujibur Rahman Science and Technology University}}, journal={{Global Journal of Researches in Engineering}}, journal={{GJRE}}2249-45960975-586110.34257/gjre, address={Cambridge, United States}, publisher={Global Journals Organisation}2135163 } @incollection{b0, , title={{Malaria outbreak prediction model using machine learning}} , author={{ VSharma } and { AKumar } and { DLakshmipanat } and { GKarajkhede }} , journal={{International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)}} 4 12 , year={2015} } @incollection{b1, , title={{Extensive Study OfIot in Healthcare Based On Machine Learning And Cloud}} , author={{ AsmitaBhowal }} , journal={{International Journal of Innovations in Engineering and Technology (IJIET)}} 12 , year={2019} } @incollection{b2, , title={{Artificial intelligence, machine learning and health systems}} , author={{ TPanch } and { PSzolovits } and { R&atun }} , journal={{Journal of global health}} 8 2 , year={2018} } @incollection{b3, , title={{Identifying the Most Appropriate Intervention Targets Using Prediction Model Based on a Machine-Learning Method: A Retrospective Analysis of a Health Promotion Program for Improving Participation in General}} , author={{ AShimoda } and { YSaito } and { COoe } and { DIchikawa } and { AIgarashi } and { TNakayama } and { ..Oyama } and { H }} , journal={{Health Check-Up. EJBI}} 14 4 , year={2018} } @book{b4, , title={{Diagnosis of Chronic Kidney Disease by}} , author={{ ASubasi } and { EAlickovic } and { JKevric }} , editor={Using Random Forest. CMBEBIH} , year={2017} 2017 } @incollection{b5, , title={{Applying spark based machine learning model on streaming big data for health status prediction}} , author={{ LRNair } and { SDShetty } and { SDShetty }} , journal={{Computers & Electrical Engineering}} 65 , year={2018} } @incollection{b6, , title={{Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures}} , author={{ KJKubota } and { JAChen } and { MALittle }} , journal={{Movement Disorders}} 31 9 , year={2016} } @incollection{b7, , title={{Urinary Polyamine Biomarker Panels with Machine-Learning Differentiated Colorectal Cancers, Benign Disease, and Healthy Controls}} , author={{ TNakajima } and { KKatsumata } and { HKuwabara } and { RSoya } and { MEnomoto } and { TIshizaki } and { MSugimoto }} , journal={{International Journal of Molecular Sciences}} 19 3 , year={2018} } @incollection{b8, , title={{Review of image processing and machine learning techniques for eye disease detection and classification}} , author={{ LUmesh } and { MMrunalini } and { SShinde }} , journal={{International Research Journal of Engineering and Technology}} 3 3 , year={2016} } @incollection{b9, , title={{A comparative study on thyroid disease detection using K-nearest neighbor and Naive Bayes classification techniques}} , author={{ KChandel } and { VKunwar } and { SSabitha } and { TChoudhury } and { SMukherjee }} , journal={{CSI Transactions on ICT}} 4 2-4 , year={2016} } @incollection{b10, , title={{Medical diagnosis system using machine learning}} , author={{ DRaval } and { DBhatt } and { MKKumhar } and { VParikh } and { D&vyas }} , journal={{International Journal of Computer Science & Communication}} 7 1 , year={2016} } @incollection{b11, , title={{An Investigation Into Machine Learning Regression Techniques for the Leaf Rust Disease Detection Using Hyperspectral Measurement}} , author={{ DAshourloo } and { HAghighi } and { AAMatkan } and { MRMobasheri } and { AMRad }} , journal={{IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}} 9 9 , year={2016} } @incollection{b12, , title={{Improving tuberculosis diagnostics using deep learning and mobile health technologies among resource-poor and marginalized communities}} , author={{ YCao } and { CLiu } and { BLiu } and { MJBrunette } and { NZhang } and { TSun } and { WHCurioso }} , booktitle={{2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies}} , year={2016. June} 9 } @incollection{b13, , title={{Artificial Intelligence in Health, Human Service Delivery and Education: A Brief Conceptual Overview}} , author={{ RandyBasham }} , journal={{Journal of Health Science}} 7 , year={2019} } @incollection{b14, , title={{Machine Learning Theory and Applications for Healthcare}} , author={{ AKhare } and { MJeon } and { IKSethi } and { BXu }} , journal={{Journal of Healthcare Engineering}} 2017 , year={2017} } @incollection{b15, , title={{Potential application of machine learning in health outcomes research and some statistical cautions}} , author={{ WHCrown }} , journal={{Value in health}} 18 2 , year={2015} } @incollection{b16, , title={{Deep learning for health informatics}} , author={{ DRavì } and { CWong } and { FDeligianni } and { MBerthelot } and { JAndreu-Perez } and { BLo } and { GZYang }} , journal={{IEEE journal of biomedical and health informatics}} 21 1 , year={2016} } @incollection{b17, , title={{Machine learning for prediction in electronic health data}} , author={{ SRose }} , journal={{JAMA network open}} 1 4 , year={2018} } @incollection{b18, , title={{Machine learning for biomarker identification in cancer researchdevelopments toward its clinical application}} , author={{ ZJagga } and { DGupta }} , journal={{Personalized medicine}} 12 4 , year={2015} } @incollection{b19, , title={{Machine learning approaches to the application of disease modifying therapy for sickle cell using classification models}} , author={{ MKhalaf } and { AJHussain } and { RKeight } and { DAl-Jumeily } and { PFergus } and { RKeenan } and { PTso }} , journal={{Neurocomputing}} 228 , year={2017} } @incollection{b20, , title={{Machine Learning in Cardiac Health Monitoring and Decision Support}} , author={{ SHijazi } and { APage } and { BKantarci } and { TSoyata }} , journal={{Computer}} 49 11 , year={2016} } @incollection{b21, , title={{Machine Learning and the Profession of Medicine}} , author={{ AMDarcy } and { AKLouie } and { LWRoberts }} , journal={{JAMA}} 6 , year={2016} } @incollection{b22, , title={{A Survey on Medical Diagnosis of Diabetes Using Machine Learning Techniques}} , author={{ AChoudhury } and { DGupta }} , booktitle={{Machine Learning and Data Analytics}} , year={2018} 9 , note={Recent Developments in} } @incollection{b23, , title={{Machine learning in heart failure}} , author={{ SEAwan } and { FSohel } and { FMSanfilippo } and { MBennamoun } and { GDwivedi }} , journal={{Current Opinion in Cardiology}} 32 , year={2017} } @incollection{b24, , title={{Big Data in Public Health: Terminology, Machine Learning, and Privacy}} , author={{ SJMooney } and { VPejaver }} , journal={{Annual Review of Public Health}} 39 1 , year={2018} } @incollection{b25, , title={{Prediction of chronic kidney disease using random forest machine learning algorithm}} , author={{ MKumar }} , journal={{International Journal of Computer Science and Mobile Computing}} 5 2 , year={2016} } @incollection{b26, , title={{Study on Cardiovascular Disease Classification Using Machine Learning Approaches}} , author={{ RSubha } and { KAnandakumar } and { A&bharathi }} , journal={{International Journal of Applied Engineering Research}} 11 6 , year={2016} } @incollection{b27, , title={{Interpretable machine learning in healthcare}} , author={{ MAAhmad } and { CEckert } and { ATeredesai }} , booktitle={{Proceedings of the 2018 ACM International Conference on Bioinformatics}} the 2018 ACM International Conference on Bioinformatics , year={2018. August} 19 } @incollection{b28, , title={{Computational health informatics in the big data age: a survey}} , author={{ RFang } and { SPouyanfar } and { YYang } and { SCChen } and { SSIyengar }} , journal={{ACM Computing Surveys (CSUR)}} 49 1 , year={2016} } @incollection{b29, , title={{The role of digital health in supporting the achievement of the Sustainable Development Goals (SDGs)}} , author={{ DNovillo-Ortiz } and { HDe Fátima Marin } and { FSaigí-Rubió }} , journal={{International Journal of Medical Informatics}} 114 , year={2018} } @incollection{b30, , title={{Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset}} , author={{ WLuo } and { TNguyen } and { MNichols } and { TTran } and { SRana } and { SGupta } and { ..Allender } and { S }} , journal={{PloS one}} 10 5 , year={2015} } @incollection{b31, , title={{Big data in public health: terminology, machine learning, and privacy}} , author={{ SJMooney } and { V&pejaver }} , journal={{Annual review of public health}} 39 , year={2018} } @incollection{b32, , title={{A comparative analysis of nonlinear machine learning algorithms for breast cancer detection}} , author={{ AABataineh }} , journal={{International Journal of Machine Learning and Computing}} 9 3 , year={2019} } @incollection{b33, , title={{Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy}} , author={{ TLange } and { De } and { PHalvorsen } and { MRiegler }} , journal={{World Journal of Gastroenterology}} 24 , year={2018} } @incollection{b34, , title={{A Survey of Machine Learning Based Approaches for Parkinson Disease Prediction}} , author={{ ShubhamBind } and { ArvindKumarTiwari } and { AnilKumar Sahani }} , journal={{International Journal of Computer Science and Information Technologies}} 6 2 , year={2015} } @incollection{b35, , title={{Diabetes mellitus affected patients classification and diagnosis through machine learning techniques}} , author={{ FMercaldo } and { VNardone } and { ASantone }} , journal={{Procedia computer science}} 112 , year={2017} } @incollection{b36, , title={{Early Diagnosis of Dementia from Clinical Data by Machine Learning Techniques}} , author={{ ASo } and { DHooshyar } and { KPark } and { HLim }} , journal={{Applied Sciences}} 7 7 651 , year={2017} } @incollection{b37, , title={{Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications}} , author={{ PThottakkara } and { TOzrazgat-Baslanti } and { BBHupf } and { PRashidi } and { PPardalos } and { PMomcilovic } and { ABihorac }} , journal={{PLOS ONE}} 11 5 , year={2016} } @incollection{b38, , title={{Heart Disease Detection by Using Machine Learning Algorithms and a Real-Time Cardiovascular Health Monitoring System}} , author={{ SNashif } and { MdRRaihan } and { MdRIslam } and { MHImam }} , journal={{World Journal of Engineering and Technology}} 6 , year={2018} } @incollection{b39, , title={{A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases}} , author={{ PMKumar } and { UGandhi }} , journal={{Computers & Electrical Engineering}} 65 , year={2018} } @incollection{b40, , title={{Machine Learning Algorithms with ROC Curve for Predicting and Diagnosing the Heart Disease}} , author={{ RKannan } and { V&vasanthi }} , booktitle={{Springer Briefs in Applied Sciences and Technology}} , year={2018} 7 } @incollection{b41, , title={{Statistical and machine learning methods for the dynamic prediction of prognosis in haematological malignancies (Doctoral dissertation}} , author={{ JLBiccler }} , journal={{Aalborg Universitetsforlag)}} 7 , year={2019. 2019} } @incollection{b42, , title={{Machine Learning Based Unified Framework for Diabetes Prediction}} , author={{ SMMahmud } and { MAHossin } and { MRAhmed } and { SR HNoori } and { MN ISarkar }} , booktitle={{Proceedings of the 2018 International Conference on Big Data Engineering and Technology}} the 2018 International Conference on Big Data Engineering and Technology , publisher={ACM} , year={2018. August} } @incollection{b43, , title={{Detection of Alzheimer's disease by displacement field and machine learning}} , author={{ YZhang } and { SWang }} , journal={{Peer J}} 3 , year={2015} } @incollection{b44, , title={{Liver disease prediction using SVM and Naïve Bayes algorithms}} , author={{ SVijayarani } and { SDhayanand }} , journal={{International Journal of Science, Engineering and Technology Research (IJSETR)}} 4 4 , year={2015} } @incollection{b45, , title={{Predicting Breast Cancer Recurrence Using Machine Learning Techniques}} , author={{ PHAbreu } and { MSSantos } and { MHAbreu } and { BAndrade } and { DCSilva }} , journal={{ACM Computing Surveys}} 49 3 , year={2016} } @incollection{b46, , title={{Heart disease prediction using machine learning and data mining technique}} , author={{ JPatel } and { DTejalupadhyay } and { SPatel }} , journal={{Heart Disease}} 7 1 , year={2015} } @incollection{b47, , title={{A Cloud Based Four-Tier Architecture for Early Detection of Heart Disease with Machine Learning Algorithms}} , author={{ MRAhmed } and { SHMahmud } and { MAHossin } and { HJahan } and { SR HNoori }} , booktitle={{2018 IEEE 4th International Conference on Computer and Communications (ICCC)}} , publisher={IEEE} , year={2018. December} } @incollection{b48, , title={{Heart Disease Diagnosis and Prediction Using Machine Learning and Data Mining Techniques: A Review}} , author={{ MLearning }} , journal={{Advances in Computational Sciences and Technology}} 10 7 , year={2017} } @incollection{b49, , title={{Prediction of depression among senior citizens using machine learning classifiers}} , author={{ IBhakta } and { ASau }} , journal={{International Journal of Computer Applications}} 144 7 , year={2016} } @incollection{b50, , title={{A machine learning model for improving healthcare services on cloud computing environment}} , author={{ AAbdelaziz } and { MElhoseny } and { ASSalama } and { AM&riad }} , journal={{Measurement}} 119 , year={2018} } @incollection{b51, , title={{Machine learning techniques for medical diagnosis of diabetes using iris images}} , author={{ PSamant } and { RAgarwal }} , journal={{Computer Methods and Programs in Biomedicine}} 157 , year={2018} } @incollection{b52, , title={{Gait and tremor investigation using machine learning techniques for the diagnosis of Parkinson disease}} , author={{ EAbdulhay } and { NArunkumar } and { KNarasimhan } and { EVellaiappan } and { VVenkatraman }} , journal={{Future Generation Computer Systems}} 83 , year={2018} } @incollection{b53, , title={{May, Predicting Diabetes in Medical Datasets Using Machine Learning Techniques}} , author={{ UAZia } and { NKhan }} , journal={{International Journal of Scientific and Engineering Research}} 8 5 , year={2017} } @incollection{b54, , title={{Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography}} , author={{ SNarula } and { KShameer } and { AMSalem Omar } and { JTDudley } and { PPSengupta }} , journal={{Journal of the American College of Cardiology}} 68 21 , year={2016} } @incollection{b55, , title={{The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model*}} , author={{ JLKoyner } and { KACarey } and { DPEdelson } and { MM&churpek }} , journal={{Critical Care Medicine}} 46 7 , year={2018} } @incollection{b56, , title={{Concealed Firearm Detection in Male and Female on Video using Machine Learning Classification: A Comparative Study}} , author={{ HMuchiri } and { IAteya } and { G&wanyembi }} , journal={{Age (Years)}} 20 } @incollection{b57, , title={{A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy}} , author={{ SS K } and { A& P }} , journal={{Journal of Medical Systems}} 41 12 , year={2017} } @incollection{b58, , title={{Identifying incipient dementia individuals using machine learning and amyloid imaging}} , author={{ SMathotaarachchi } and { TAPascoal } and { MShin } and { ALBenedet } and { MSKang } and { TBeaudry } and { PRosa-Neto }} , journal={{Neurobiology of Aging}} 59 , year={2017} } @incollection{b59, , title={{Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease}} , author={{ AOrtiz } and { JMunilla } and { JMGórriz } and { J&ramírez }} , journal={{International Journal of Neural Systems}} 26 07 , year={2016} } @incollection{b60, , title={{Disease Prediction by Machine Learning Over Big Data from Healthcare Communities}} , author={{ MChen } and { YHao } and { KHwang } and { LWang } and { LWang }} , journal={{IEEE Access}} 5 , year={2017} } @incollection{b61, , title={{Coronary Heart Disease Diagnosis using Deep Neural Networks}} , author={{ KHMiaoa } and { JH&miaoa }} , journal={{INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS}} 9 10 , year={2018} } @incollection{b62, , title={{Prediction of heart disease using machine learning algorithms}} , author={{ SNikhar } and { AM&karandikar }} , journal={{International Journal of Advanced Engineering}} 2 6 , year={2016} , note={Management and Science} } @incollection{b63, , title={{Artificial intelligence: opportunities and risks for public health}} , author={{ TPanch } and { JPearson-Stuttard } and { FGreaves } and { R&atun }} , journal={{The Lancet Digital Health}} 1 1 , year={2019} } @incollection{b64, , title={{A Machine Learning Approach for Stress Detection using a Wireless Physical Activity Tracker}} , author={{ BPadmaja } and { VRPrasad } and { KVSunitha }} , journal={{Int. J. Mach. Learn. Comput}} 8 , year={2018} } @incollection{b65, , title={{Rise of the machines: advances in deep learning for cancer diagnosis}} , author={{ ABLevine } and { CSchlosser } and { JGrewal } and { RCoope } and { SJJones } and { SYip }} , journal={{Trends in cancer}} 5 , year={2019} } @incollection{b66, , title={{Next-Generation Sequencing of Circulating Tumor DNA for Early Cancer Detection}} , author={{ AMAravanis } and { MLee } and { RDKlausner }} , journal={{Cell}} 168 4 , year={2017} } @incollection{b67, , title={{Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes}} , author={{ JKo } and { NBhagwat } and { SSYee } and { NOrtiz } and { ASahmoud } and { TBlack } and { DIssadore }} , journal={{ACS Nano}} 11 11 , year={2017} } @incollection{b68, , title={{Data mining classification algorithms for kidney disease prediction}} , author={{ SVijayarani } and { S&dhayanand }} , journal={{International Journal on Cybernetics & Informatics (IJCI)}} 4 4 , year={2015} } @book{b69, , author={{ RNBryan }} , title={{Machine Learning Applied to Alzheimer Disease. Radiology}} , year={2016} 281 } @incollection{b70, , title={{A Machine-Learning Algorithm Toward Color Analysis for Chronic Liver Disease Classification, Employing Ultrasound Shear Wave Elastography}} , author={{ IGatos } and { STsantis } and { SSpiliopoulos } and { DKarnabatidis } and { ITheotokas } and { PZoumpoulis } and { GCKagadis }} , journal={{Ultrasound in Medicine & Biology}} 43 9 , year={2017} } @incollection{b71, , title={{Deep ensemble learning of sparse regression models for brain disease diagnosis}} , author={{ H.-ISuk } and { S.-WLee } and { DShen }} , journal={{Medical Image Analysis}} 37 , year={2017} } @incollection{b72, , title={{An analytical method for diseases prediction using machine learning techniques}} , author={{ MNilashi } and { OIbrahim } and { HAhmadi } and { LShahmoradi }} , journal={{Computers & Chemical Engineering}} 106 , year={2017} } @incollection{b73, , title={{A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients}} , author={{ AMannini } and { DTrojaniello } and { ACereatti } and { ASabatini }} , journal={{Sensors}} 16 1 , year={2016} } @incollection{b74, , title={{Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier}} , author={{ CVSubbulakshmi } and { SN&deepa }} , journal={{The Scientific World Journal}} 2015 , year={2015} } @incollection{b75, , title={{Machine learning techniques for thyroid disease diagnosis-a review}} , author={{ SRazia } and { MNRao }} , journal={{Indian J Sci Technol}} 9 28 , year={2016} } @incollection{b76, , title={{Prediction of hospitalization due to heart diseases by supervised learning methods}} , author={{ WDai } and { TSBrisimi } and { WGAdams } and { TMela } and { VSaligrama } and { IC&paschalidis }} , journal={{International Journal of Medical Informatics}} 84 3 , year={2015} } @incollection{b77, , title={{Artificial Intelligence and Healthcare}} , author={{ SalemHamoud } and { HAlanazi }} , journal={{International Journal of Artificial Intelligence and Machine Learning}} 1 } @incollection{b78, , title={{Applying spark based machine learning model on streaming big data for health status prediction}} , author={{ LRNair } and { SDShetty } and { SDShetty }} , journal={{Computers & Electrical Engineering}} 65 , year={2018} } @incollection{b79, , title={{Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression}} , author={{ JFDipnall } and { JAPasco } and { MBerk } and { LJWilliams } and { SDodd } and { FNJacka } and { DMeyer }} , journal={{PLOS ONE}} 11 2 , year={2016} } @incollection{b80, , title={{A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression}} , author={{ SPerveen } and { MShahbaz } and { KKeshavjee } and { A&guergachi }} , journal={{Scientific Reports}} 8 1 , year={2018} } @incollection{b81, , title={{Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants}} , author={{ MSchubach } and { MRe } and { PNRobinson } and { G&valentini }} , journal={{Scientific Reports}} 7 1 , year={2017} } @incollection{b82, , title={{Performance analysis of classification algorithms on early detection of liver disease}} , author={{ MAbdar } and { MZomorodi-Moghadam } and { RDas } and { I.-HTing }} , journal={{Expert Systems with Applications}} 67 , year={2017} } @incollection{b83, , title={{Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification}} , author={{ IArganda-Carreras } and { VKaynig } and { CRueden } and { KWEliceiri } and { JSchindelin } and { ACardona } and { HSebastian Seung }} , journal={{Bioinformatics}} 33 15 , year={2017} } @book{b84, , author={{ KMJohnson } and { HEJohnson } and { YZhao } and { DADowe } and { LHStaib }} , title={{Scoring of Coronary Artery Disease Characteristics on Coronary CTAngiograms by Using Machine Learning. Radiology, 182061}} , year={2019} 29 } @book{b85, , title={{An Ensemble Machine Learning Model For the Early Detection of sepsis from Clinical Data}} , author={{ MFu } and { JYuan } and { MLu } and { PHong } and { MZeng }} } @incollection{b86, , title={{}} , journal={{Platelets}} 199 } @incollection{b87, , title={{Predicting Renal Failure Progression in Chronic Kidney Disease Using Integrated Intelligent Fuzzy Expert System}} , author={{ JNorouzi } and { AYadollahpour } and { SAMirbagheri } and { MMMazdeh } and { SAHosseini }} , journal={{Computational and Mathematical Methods in Medicine}} 2016 , year={2016} } @incollection{b88, , title={{Development of machine learning models for diagnosis of glaucoma}} , author={{ SJKim } and { KJCho } and { SOh }} , journal={{PLOS ONE}} 12 5 , year={2017} } @incollection{b89, , title={{Machine Learning Algorithms for Risk Prediction of Severe Hand-Foot-Mouth Disease in Children}} , author={{ BZhang } and { XWan } and { FOuyang } and { YDong } and { DLuo } and { JLiu } and { SZhang }} , journal={{Scientific Reports}} 7 1 , year={2017} } @incollection{b90, , title={{Classifier Model Based on Machine Learning Algorithms: Application to Differential Diagnosis of Suspicious Thyroid Nodules via Sonography}} , author={{ HWu } and { ZDeng } and { BZhang } and { QLiu } and { JChen }} , journal={{American Journal of Roentgenology}} 207 4 , year={2016} } @incollection{b91, , title={{Machine learning applications in cancer prognosis and prediction}} , author={{ KKourou } and { TPExarchos } and { KPExarchos } and { MVKaramouzis } and { DI&fotiadis }} , journal={{Computational and Structural Biotechnology Journal}} 13 , year={2015} } @incollection{b92, , title={{A survey on diabetes mellitus prediction using machine learning techniques}} , author={{ CThiyagarajan } and { KAKumar } and { ABharathi }} , journal={{International Journal of Applied Engineering Research}} 11 3 , year={2016} } @incollection{b93, , title={{Evaluation of diagnostic tests in human health and disease}} , author={{ IJMartins }} , journal={{J Clin Path Lab Med}} 2 1 , year={2018. 2018} } @incollection{b94, , title={{Survey of machine learning algorithms for disease diagnostic}} , author={{ MFatima } and { MPasha }} , journal={{Journal of Intelligent Learning Systems and Applications}} 9 01 , year={2017} } @book{b95, , title={{Disease Prediction by Machine Learning from Healthcare Communities}} , author={{ SJadhav } and { RKasar } and { NLade } and { MPatil } and { S&kolte }} , year={2019} } @incollection{b96, , title={{Deep learning for health informatics}} , author={{ DRavì } and { CWong } and { FDeligianni } and { MBerthelot } and { JAndreu-Perez } and { BLo } and { GZYang }} , journal={{IEEE journal of biomedical and health informatics}} 21 1 , year={2016} } @incollection{b97, , title={{Machine Learning in Cardiac Health Monitoring and Decision Support}} , author={{ SHijazi } and { APage } and { BKantarci } and { T&soyata }} , journal={{Computer}} 49 11 , year={2016} } @incollection{b98, , title={{Machine Learning and Data Mining Methods in Diabetes Research}} , author={{ IKavakiotis } and { OTsave } and { ASalifoglou } and { NMaglaveras } and { IVlahavas } and { IChouvarda }} , journal={{Computational and Structural Biotechnology Journal}} 15 , year={2017} } @incollection{b99, , title={{A machine learning-based framework to identify type 2 diabetes through electronic health records}} , author={{ TZheng } and { WXie } and { LXu } and { XHe } and { YZhang } and { MYou } and { YChen }} , journal={{International Journal of Medical Informatics}} 97 , year={2017} } @incollection{b100, , title={{Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women with Breast Cancer}} , author={{ BEhteshamibejnordi } and { MVeta } and { PJohannes Van Diest } and { BVan Ginneken } and { NKarssemeijer } and { GLitjens } and { Balkenhol }} , journal={{JAMA}} 318 , year={2017} } @incollection{b101, , title={{Automated Identification of Diabetic Retinopathy Using Deep Learning}} , author={{ RGargeya } and { T&leng }} , journal={{Ophthalmology}} 124 7 , year={2017} } @incollection{b102, , title={{Machine learning approaches in medical image analysis: From detection to diagnosis}} , author={{ MDe Bruijne }} , journal={{Medical Image Analysis}} 33 , year={2016} } @incollection{b103, , title={{Detecting Cardiovascular Disease from Mammograms With Deep Learning}} , author={{ JWang } and { HDing } and { FABidgoli } and { BZhou } and { CIribarren } and { SMolloi } and { P&baldi }} , journal={{IEEE Transactions on Medical Imaging}} 36 5 , year={2017} } @book{b104, , author={{ SStanly } and { RKMalar }} , title={{Earlier Diabetic Retinopathy Detection Using Advanced Pre-Processing Methods and SVM Classification}} , year={2019} 6 } @incollection{b105, , title={{A machine learning model for improving healthcare services on cloud computing environment}} , author={{ AAbdelaziz } and { MElhoseny } and { ASSalama } and { AM&riad }} , journal={{Measurement}} 119 , year={2018} } @incollection{b106, , title={{M4CVD: Mobile Machine Learning Model for Monitoring Cardiovascular Disease}} , author={{ OBoursalie } and { RSamavi } and { TEDoyle }} , journal={{Procedia Computer Science}} 63 , year={2015} } @incollection{b107, , title={{Big Data and Machine Learning in Health Care}} , author={{ ALBeam } and { IS&kohane }} , journal={{JAMA}} 319 13 , year={2018} } @incollection{b108, , title={{Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort}} , author={{ DLeightley } and { VWilliamson } and { JDarby } and { NTFear }} , journal={{Journal of Mental Health}} 28 1 , year={2019} } @incollection{b109, , title={{Imaging and machine learning techniques for diagnosis of Alzheimer's disease}} , author={{ GMirzaei } and { AAdeli } and { HAdeli }} , journal={{Reviews in the Neurosciences}} 27 8 , year={2016} } @incollection{b110, , title={{An unsupervised machine learning model for discovering latent infectious diseases using social media data}} , author={{ SLim } and { CSTucker } and { S&kumara }} , journal={{Journal of Biomedical Informatics}} 66 , year={2017} } @incollection{b111, , title={{Developing a dengue forecast model using machine learning: A case study in China}} , author={{ PGuo } and { TLiu } and { QZhang } and { LWang } and { JXiao } and { QZhang } and { WMa }} , journal={{PLOS Neglected Tropical Diseases}} 11 10 , year={2017} } @incollection{b112, , title={{Congestive heart failure detection using random forest classifier}} , author={{ ZMasetic } and { ASubasi }} , journal={{Computer Methods and Programs in Biomedicine}} 130 , year={2016} } @incollection{b113, , title={{Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis}} , author={{ HAsri } and { HMousannif } and { HAMoatassime } and { TNoel }} , journal={{Procedia Computer Science}} 83 , year={2016} } @incollection{b114, , title={{Using Machine Learning to Predict Swine Movements within a Regional Program to Improve Control of Infectious Diseases in the US}} , author={{ PValdes-Donoso } and { KVanderwaal } and { LSJarvis } and { SRWayne } and { AMPerez }} , journal={{Frontiers in Veterinary Science}} 4 , year={2017} } @incollection{b115, , title={{Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning}} , author={{ JBetancur } and { YOtaki } and { MMotwani } and { MBFish } and { MLemley } and { DDey } and { PJSlomka }} , journal={{JACC: Cardiovascular Imaging}} 11 7 , year={2018} } @incollection{b116, , title={{Skin Lesion Classification using Machine Learning Algorithms}} , author={{ IAOzkan } and { MKoklu }} , journal={{International Journal of Intelligent Systems and Applications in Engineering}} 5 4 , year={2017} } @incollection{b117, , title={{Using machine learning tool in classification of breast cancer}} , author={{ LAbdel-Ilah } and { H?ahinbegovi? }} , journal={{CMBEBIH}} 2017 , year={2017} } @incollection{b118, , title={{An Investigation Into Machine Learning Regression Techniques for the Leaf Rust Disease Detection Using Hyperspectral Measurement}} , author={{ DAshourloo } and { HAghighi } and { AAMatkan } and { MRMobasheri } and { AMRad }} , journal={{IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}} 9 9 , year={2016} } @incollection{b119, , title={{Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES}} , author={{ SKPark } and { ZZhao } and { BMukherjee }} , journal={{Environmental Health}} 16 1 , year={2017} }