Medical Internet of things using machine learning algorithms for lung cancer detection

This paper empirically evaluates the several machine learning algorithms adaptable for lung cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for predicting diffe...

[1]  Yixin Chen,et al.  Predicting Hospital Readmission via Cost-Sensitive Deep Learning , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[2]  Yuichi Motai,et al.  Intra- and Inter-Fractional Variation Prediction of Lung Tumors Using Fuzzy Deep Learning , 2016, IEEE Journal of Translational Engineering in Health and Medicine.

[3]  Yifei Zhang,et al.  An Automated Strategy for Early Risk Identification of Sudden Cardiac Death by Using Machine Learning Approach on Measurable Arrhythmic Risk Markers , 2019, IEEE Access.

[4]  Karim Keshavjee,et al.  Metabolic Syndrome and Development of Diabetes Mellitus: Predictive Modeling Based on Machine Learning Techniques , 2019, IEEE Access.

[5]  Ulisses Braga-Neto,et al.  Severe Dengue Prognosis Using Human Genome Data and Machine Learning , 2019, IEEE Transactions on Biomedical Engineering.

[6]  M. Mansourian,et al.  A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR) Using Optimized Ensemble Learning , 2016, Computational and structural biotechnology journal.

[7]  Alok N. Choudhary,et al.  Colon cancer survival prediction using ensemble data mining on SEER data , 2013, 2013 IEEE International Conference on Big Data.

[8]  José David Martín-Guerrero,et al.  A new machine learning approach for predicting the response to anemia treatment in a large cohort of End Stage Renal Disease patients undergoing dialysis , 2015, Comput. Biol. Medicine.

[9]  Jingyu Hou,et al.  Cancer adjuvant chemotherapy prediction model for non-small cell lung cancer. , 2019, IET systems biology.

[10]  José David Martín-Guerrero,et al.  A new approach based on Machine Learning for predicting corneal curvature (K1) and astigmatism in patients with keratoconus after intracorneal ring implantation , 2014, Comput. Methods Programs Biomed..

[11]  Mingzhou Song,et al.  A Fast Exact Functional Test for Directional Association and Cancer Biology Applications , 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[12]  Marek Lubicz,et al.  Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients , 2014, Appl. Soft Comput..

[13]  Robert-Jan Sips,et al.  Utilizing Data Mining for Predictive Modeling of Colorectal Cancer Using Electronic Medical Records , 2014, Brain Informatics and Health.

[14]  Gautam Srivastava,et al.  Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques , 2019, IEEE Access.

[15]  Hosik Choi,et al.  Gene selection and prediction for cancer classification using support vector machines with a reject option , 2011, Comput. Stat. Data Anal..

[16]  Aurangzeb Khan,et al.  An Automated Diagnostic System for Heart Disease Prediction Based on ${\chi^{2}}$ Statistical Model and Optimally Configured Deep Neural Network , 2019, IEEE Access.

[17]  Conrad Bessant,et al.  Support vector machine ensembles for breast cancer type prediction from mid-FTIR micro-calcification spectra , 2011 .

[18]  Pablo Moreno-Ger,et al.  Explainable Prediction of Chronic Renal Disease in the Colombian Population Using Neural Networks and Case-Based Reasoning , 2019, IEEE Access.

[19]  Dursun Delen,et al.  Predicting breast cancer survivability: a comparison of three data mining methods , 2005, Artif. Intell. Medicine.

[20]  Jiadong Ren,et al.  DMP_MI: An Effective Diabetes Mellitus Classification Algorithm on Imbalanced Data With Missing Values , 2019, IEEE Access.

[21]  Jayadeep Pati,et al.  Gene Expression Analysis for Early Lung Cancer Prediction Using Machine Learning Techniques: An Eco-Genomics Approach , 2019, IEEE Access.

[22]  Zarko Milosevic,et al.  Machine Learning Approach for Predicting Wall Shear Distribution for Abdominal Aortic Aneurysm and Carotid Bifurcation Models , 2018, IEEE Journal of Biomedical and Health Informatics.

[23]  Yuehong Yin,et al.  The internet of things in healthcare: An overview , 2016, J. Ind. Inf. Integr..

[24]  DongFeng,et al.  Advanced internet of things for personalised healthcare systems , 2017 .

[25]  Hongming Cai,et al.  Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services , 2014, IEEE Transactions on Industrial Informatics.

[26]  Freddie Åström,et al.  A parallel neural network approach to prediction of Parkinson's Disease , 2011, Expert Syst. Appl..

[27]  Nandita Mitra,et al.  A Neighborhood-Wide Association Study (NWAS): Example of prostate cancer aggressiveness , 2017, PloS one.

[28]  Burcu Çarklı Yavuz,et al.  Prediction of Protein Secondary Structure With Clonal Selection Algorithm and Multilayer Perceptron , 2018, IEEE Access.

[29]  Boncho Ku,et al.  Prediction of Fasting Plasma Glucose Status Using Anthropometric Measures for Diagnosing Type 2 Diabetes , 2014, IEEE Journal of Biomedical and Health Informatics.

[30]  Cemil Kuzey,et al.  Visa trial of international trade: evidence from support vector machines and neural networks , 2020 .

[31]  Ashish Khanna,et al.  Boosted neural network ensemble classification for lung cancer disease diagnosis , 2019, Appl. Soft Comput..

[32]  Venkatesh Saligrama,et al.  Prediction of hospitalization due to heart diseases by supervised learning methods , 2015, Int. J. Medical Informatics.

[33]  Mahmood Fathy,et al.  Combining Supervised and Unsupervised Learning for Improved miRNA Target Prediction , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[34]  Khalil Maalmi,et al.  A new Internet of Things architecture for real-time prediction of various diseases using machine learning on big data environment , 2019, Journal of Big Data.

[35]  Xiuzhen Cheng,et al.  Developing Prognostic Systems of Cancer Patients by Ensemble Clustering , 2009, Journal of biomedicine & biotechnology.

[36]  Amber Young,et al.  A data-driven approach to predicting diabetes and cardiovascular disease with machine learning , 2019, BMC Medical Informatics and Decision Making.

[37]  Dursun Delen,et al.  Predicting the graft survival for heart-lung transplantation patients: An integrated data mining methodology , 2009, Int. J. Medical Informatics.

[38]  James A. Bartholomai,et al.  Prediction of lung cancer patient survival via supervised machine learning classification techniques , 2017, Int. J. Medical Informatics.

[39]  S. Lam,et al.  Near‐infrared Raman spectroscopy for optical diagnosis of lung cancer , 2003, International journal of cancer.

[40]  Robert J. Gillies,et al.  Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features , 2014, IEEE Access.

[41]  Yilmaz Kaya,et al.  A hybrid decision support system based on rough set and extreme learning machine for diagnosis of hepatitis disease , 2013, Appl. Soft Comput..

[42]  Mark S. Redfern,et al.  Extraction of Stride Events From Gait Accelerometry During Treadmill Walking , 2015, IEEE Journal of Translational Engineering in Health and Medicine.

[43]  P. K. Anooj,et al.  Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules , 2012, J. King Saud Univ. Comput. Inf. Sci..

[44]  Richard Staba,et al.  Multimodal data and machine learning for surgery outcome prediction in complicated cases of mesial temporal lobe epilepsy , 2015, Comput. Biol. Medicine.

[45]  George Dimitoglou,et al.  Comparison of the C4.5 and a Naive Bayes Classifier for the Prediction of Lung Cancer Survivability , 2012, ArXiv.

[46]  A. Esmaeili,et al.  Prediction of GABAA receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine. , 2011, Journal of theoretical biology.

[47]  Wei Zhong,et al.  Clinical charge profiles prediction for patients diagnosed with chronic diseases using Multi-level Support Vector Machine , 2012, Expert Syst. Appl..

[48]  Hai-Long Wu,et al.  Variable selection using probability density function similarity for support vector machine classification of high-dimensional microarray data. , 2009, Talanta.

[49]  Dong-Hee Koh,et al.  Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis , 2010, Safety and health at work.

[50]  Jing Li,et al.  A Novel Positive Transfer Learning Approach for Telemonitoring of Parkinson’s Disease , 2019, IEEE Transactions on Automation Science and Engineering.

[51]  Dursun Delen,et al.  Knowledge Extraction from Prostate Cancer Data , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[52]  Giuseppe Aceto,et al.  Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0 , 2020, J. Ind. Inf. Integr..

[53]  Chao Tan,et al.  Early prediction of lung cancer based on the combination of trace element analysis in urine and an Adaboost algorithm. , 2009, Journal of pharmaceutical and biomedical analysis.

[54]  Maarten De Vos,et al.  Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data , 2019, IEEE Transactions on Biomedical Engineering.

[55]  Yang Lu,et al.  Artificial intelligence: a survey on evolution, models, applications and future trends , 2019, Journal of Management Analytics.

[56]  Lalith Polepeddi,et al.  Colon cancer survival prediction using ensemble data mining on SEER data , 2013, 2013 IEEE International Conference on Big Data.

[57]  Jong Yeol Kim,et al.  Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning , 2016, IEEE Journal of Biomedical and Health Informatics.

[58]  John Salvatier,et al.  Theano: A Python framework for fast computation of mathematical expressions , 2016, ArXiv.

[59]  Ashish Anand,et al.  Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates. , 2009, Journal of theoretical biology.

[60]  Takuya Akiba,et al.  Chainer: A Deep Learning Framework for Accelerating the Research Cycle , 2019, KDD.

[61]  Jonathan H. Chan,et al.  Pathway activity transformation for multi-class classification of lung cancer datasets , 2015, Neurocomputing.

[62]  Dimitrios Hristu-Varsakelis,et al.  Machine learning-based classification of simple drawing movements in Parkinson's disease , 2017, Biomed. Signal Process. Control..

[63]  Nishtha Hooda,et al.  Big Data Deep Learning Framework using Keras: A Case Study of Pneumonia Prediction , 2018, 2018 4th International Conference on Computing Communication and Automation (ICCCA).

[64]  Hong Yan,et al.  An Eigen-Binding Site Based Method for the Analysis of Anti-EGFR Drug Resistance in Lung Cancer Treatment , 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[65]  Cheng Liang,et al.  Collective Prediction of Disease-Associated miRNAs Based on Transduction Learning , 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[66]  Asad Malik,et al.  Feature Selection Based on L1-Norm Support Vector Machine and Effective Recognition System for Parkinson’s Disease Using Voice Recordings , 2019, IEEE Access.

[67]  Wu He,et al.  Internet of Things in Industries: A Survey , 2014, IEEE Transactions on Industrial Informatics.

[68]  He He,et al.  GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing , 2020, J. Mach. Learn. Res..

[69]  Dursun Delen,et al.  Analysis of cancer data: a data mining approach , 2009, Expert Syst. J. Knowl. Eng..

[70]  Min Chen,et al.  Disease Prediction by Machine Learning Over Big Data From Healthcare Communities , 2017, IEEE Access.

[71]  Pol Cirujeda,et al.  A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT , 2016, IEEE Transactions on Medical Imaging.

[72]  Alok N. Choudhary,et al.  A lung cancer outcome calculator using ensemble data mining on SEER data , 2011, BIOKDD '11.

[73]  Hiroshi Kimura,et al.  Changes of tumor size and tumor contrast enhancement during radiotherapy for non-small-cell lung cancer may be suggestive of treatment response. , 2012, Journal of radiation research.

[74]  Zoya Khalid,et al.  Prediction of HIV Drug Resistance by Combining Sequence and Structural Properties , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[75]  Mehmet Fatih Akay,et al.  Support vector machines combined with feature selection for breast cancer diagnosis , 2009, Expert Syst. Appl..

[76]  Amin M. Abbosh,et al.  Lung cancer detection using frequency-domain microwave imaging , 2015 .

[77]  Yu-Dong Yao,et al.  Ensemble Learners of Multiple Deep CNNs for Pulmonary Nodules Classification Using CT Images , 2019, IEEE Access.

[78]  Chip M. Lynch,et al.  Application of unsupervised analysis techniques to lung cancer patient data , 2017, PloS one.

[79]  Paul Rad,et al.  Distributed machine learning cloud teleophthalmology IoT for predicting AMD disease progression , 2019, Future Gener. Comput. Syst..

[80]  Denise R. Aberle,et al.  Using Sequential Decision Making to Improve Lung Cancer Screening Performance , 2019, IEEE Access.

[81]  R. Altman,et al.  A new disease-specific machine learning approach for the prediction of cancer-causing missense variants. , 2011, Genomics.

[82]  Ling Li,et al.  Down Syndrome Prediction Using a Cascaded Machine Learning Framework Designed for Imbalanced and Feature-correlated Data , 2019, IEEE Access.

[83]  Ganjar Alfian,et al.  Development of Disease Prediction Model Based on Ensemble Learning Approach for Diabetes and Hypertension , 2019, IEEE Access.

[84]  Gang Wang,et al.  A new hybrid method based on local fisher discriminant analysis and support vector machines for hepatitis disease diagnosis , 2011, Expert Syst. Appl..

[85]  Wei Qian,et al.  Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients , 2016, IEEE Transactions on Biomedical Engineering.

[86]  Abdulhamit Subasi,et al.  Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines , 2012, Comput. Biol. Medicine.

[87]  Bermseok Oh,et al.  Development of a Predictive Model for Type 2 Diabetes Mellitus Using Genetic and Clinical Data , 2011, Osong public health and research perspectives.

[88]  Mehrbakhsh Nilashi,et al.  An analytical method for diseases prediction using machine learning techniques , 2017, Comput. Chem. Eng..

[89]  Yong Xiang,et al.  Lung cancer prediction from microarray data by gene expression programming. , 2016, IET systems biology.

[90]  Denise R. Aberle,et al.  Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network , 2016, Artif. Intell. Medicine.

[91]  Trevor Darrell,et al.  Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.

[92]  Lida Xu,et al.  The Internet of Things (IoT): Informatics methods for IoT-enabled health care , 2018, J. Biomed. Informatics.

[93]  Xiaohong Guan,et al.  An SVM-based machine learning method for accurate internet traffic classification , 2010, Inf. Syst. Frontiers.

[94]  Geyong Min,et al.  Advanced internet of things for personalised healthcare systems: A survey , 2017, Pervasive Mob. Comput..

[95]  Austin H. Chen,et al.  A novel support vector sampling technique to improve classification accuracy and to identify key genes of leukaemia and prostate cancers , 2011, Expert Syst. Appl..

[96]  Issam El Naqa,et al.  Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer , 2019, IEEE Transactions on Radiation and Plasma Medical Sciences.

[97]  Dayou Liu,et al.  A support vector machine classifier with rough set-based feature selection for breast cancer diagnosis , 2011, Expert Syst. Appl..

[98]  Dinggang Shen,et al.  Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data , 2015, NeuroImage.

[99]  Jun Ni,et al.  Mining and Integrating Reliable Decision Rules for Imbalanced Cancer Gene Expression Data Sets , 2012 .

[100]  A. Jemal,et al.  Global Cancer Statistics , 2011 .

[101]  Alexander Wong,et al.  SISC: End-to-End Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells , 2019, IEEE Access.

[102]  Mehmet Engin,et al.  Early prostate cancer diagnosis by using artificial neural networks and support vector machines , 2009, Expert Syst. Appl..

[103]  Jiadong Ren,et al.  Health Data Driven on Continuous Blood Pressure Prediction Based on Gradient Boosting Decision Tree Algorithm , 2019, IEEE Access.

[104]  Jun Zhang,et al.  Prediction of Lung Motion From Four-Dimensional Computer Tomography (4DCT) Images Using Bayesian Registration and Trajectory Modelling , 2018, IEEE Access.

[105]  Amr Badr,et al.  A Hybridized Feature Selection and Extraction Approach for Enhancing Cancer Prediction Based on DNA Methylation , 2018, IEEE Access.

[106]  Fulong Chen,et al.  Coupling a Fast Fourier Transformation With a Machine Learning Ensemble Model to Support Recommendations for Heart Disease Patients in a Telehealth Environment , 2017, IEEE Access.

[107]  Sundaram Suresh,et al.  Parkinson's disease prediction using gene expression - A projection based learning meta-cognitive neural classifier approach , 2013, Expert Syst. Appl..

[108]  Omar S. Al-Kadi,et al.  Texture Analysis of Aggressive and Nonaggressive Lung Tumor CE CT Images , 2008, IEEE Transactions on Biomedical Engineering.

[109]  Dong-Ling Tong,et al.  Hybrid genetic algorithm-neural network: Feature extraction for unpreprocessed microarray data , 2011, Artif. Intell. Medicine.

[110]  Mark A. Anastasio,et al.  Treatment Outcome Prediction for Cancer Patients Based on Radiomics and Belief Function Theory , 2019, IEEE Transactions on Radiation and Plasma Medical Sciences.

[111]  Kuo Chi-Hsien,et al.  Applying machine learning to market analysis: Knowing your luxury consumer , 2019, Journal of Management Analytics.

[112]  Andrew P. Bradley,et al.  Intelligible Support Vector Machines for Diagnosis of Diabetes Mellitus , 2010, IEEE Transactions on Information Technology in Biomedicine.

[113]  Igor Jurisica,et al.  Data mining for case-based reasoning in high-dimensional biological domains , 2005, IEEE Transactions on Knowledge and Data Engineering.

[114]  Nikhil Ketkar,et al.  Deep Learning with Python , 2017 .

[115]  Robert J. Gillies,et al.  Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening , 2018, IEEE Access.

[116]  Srinivasan Ramakrishnan,et al.  Prediction of cancer using customised fuzzy rough machine learning approaches , 2019, Healthcare technology letters.

[117]  Jingyu Hou,et al.  Prediction of NSCLC recurrence from microarray data with GEP. , 2017, IET systems biology.

[118]  Shancang Li,et al.  5G Internet of Things: A survey , 2018, J. Ind. Inf. Integr..

[119]  Lida Xu,et al.  IoT-Based Smart Rehabilitation System , 2014, IEEE Transactions on Industrial Informatics.

[120]  Martín Abadi,et al.  TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.

[121]  Safdar Ali,et al.  Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines , 2014, Comput. Methods Programs Biomed..