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Vol. 2 No. 01 (2021)

Articles

The Role of Machine Learning Algorithms for Diagnosing Diseases

https://doi.org/10.38094/jastt20179

Published 2021-03-19

  • Ibrahim Mahmood Ibrahim
    • ,
  • Adnan Mohsin Abdulazeez

Ibrahim Mahmood Ibrahim
Technical College of Informatics-Akre, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Adnan Mohsin Abdulazeez
Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Abstract

Nowadays, machine learning algorithms have become very important in the medical sector, especially for diagnosing disease from the medical database. Many companies using these techniques for the early prediction of diseases and enhance medical diagnostics. The motivation of this paper is to give an overview of the machine learning algorithms that are applied for the identification and prediction of many diseases such as Naïve Bayes, logistic regression, support vector machine, K-nearest neighbor, K-means clustering, decision tree, and random forest. In this work, many previous studies were reviewed that used machine learning algorithms for detecting various diseases in the medical area in the last three years. A comparison is provided concerning these algorithms, assessment processes, and the obtained results. Finally, a discussion of the previous works is presented.

Keywords

Disease Diagnostics, Machine Learning, Classification Algorithm

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References

  1. Shaik Razia, P.Swathi Prathyusha, N.Vamsi Krishna, N.Sathya Sumana, "A Review on Disease Diagnosis Using Machine Learning Techniques," International Journal of Pure and Applied Mathematics, Volume 117, No. 16, 2017..
  2. Diyar Qader Zeebaree, Habibollah Haron, Adnan Mohsin Abdulazeez, and Dilovan Asaad Zebari, "Trainable Model Based on New Uniform LBP Feature to Identify the Risk of the Breast Cancer". In 2019 International Conference on Advanced Science and Engineering (I.C.O.A.S.E.) (pp. 106-111). IEEE, April 2019.
  3. Iswanto Iswanto, E. Laxmi Lydia, K. Shankar, Phong Thanh Nguyen, Wahidah Hashim, Andino, "Identifying Diseases and Diagnosis using Machine Learning", International Journal of Engineering and Advanced Technology, Vol. 8, August 2019.
  4. Reem A. Alassaf, and et al, "Preemptive Diagnosis of Chronic Kidney Disease Using Machine Learning Techniques", International Conference on innovations in Information Technology (I.T.), IEEE, 2018.
  5. Gopi Battineni, Getu Gamo Sagaro, Nalini Chinatalapudi and Francesco Amenta, "Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis", Journal of Personalized Medicine, 2020.
  6. Diyar Qader Zeebare, Habibollah Haron, Adnan Mohsin Abdulazeez and Dilovan Asaad Zebari, "Machine learning and Region Growing for Breast Cancer Segmentation", International Conference on Advanced Science and Engineering, IEEE, 2019.
  7. Hossam Meshref, "Cardiovascular Disease Diagnosis: A Machine Learning Interpretation Approach", International Journal of Advanced Computer Science and Applications, Vol. 10, No. 12, 2019.
  8. Joel Jacob, Joseph Chakkalakal Mathew, Johns Mathew and Elizabeth Issac, "Diagnosis of Liver Disease Using Machine Learning Techniques", International Research Journal of Engineering and Technology, Vol. 05, Issue: 04, Apr-2018.
  9. Siddhesh Iyer, Shivkumar Thevar, Priyamurgan Guruswamy, Ujwala Ravale, "Heart Disease Prediction Using Machine Learning", International Research Journal of Modernization in Engineering Technology and Science, Vol. 02, Issue:07, July 2020.
  10. Dilovan Asaad Zebari, Diyar Qader Zeebaree, Adnan Mohsin Abdulazeez, Habibollah Haron, and Haza Nuzly Abdull Hamed, "Improved Threshold Based and Trainable Fully Automated Segmentation for Breast Cancer Boundary and Pectoral Muscle in Mammogram Images, IEEE Access, Vol.8, 2020.
  11. Sneha Grampurohit and Chetan Sagarnal, "Disease Prediction using Machine Learning Algorithms" International Conference for Emerging Technology (I.N.C.E.T.), Belgaum, India. Jun 5-7, 2020.
  12. Pahulpreet Singh Kohli and Shriya Arora, "Application of Machine Learning in Disease Prediction", International Conference on Computing Communication and Automation (I.C.C.C.A.), IEEE, 2018.
  13. Adnan Mohsin Abdulazeez, Baraa Wasfi Salim, Diyar Qader Zeebaree, and Dana Doghramachi, "Comparison of VPN Protocols at Network Layer Focusing on Wire Guard Protocol", iJIM, Vol. 14, No. 18, 2020.
  14. Berina Alic, Lejla Gurbeta and Almir Badnjevic, “Machine Learning Techniques for Classification of Diabetes and Cardiovascular Diseases”, 6th Mediterranean Conference on Embedded Computing, 2017.
  15. Divya Jain and Vijendra Singh, “Feature selection and classification systems for chronic disease prediction: A review”, Elsevir, 2018.
  16. Huseyin Polat, Homay Danaei Mehr and Aydin Cetin, “Diagnosis of Chronic Kidney Disease Based on Support Vector Machine by Feature Selection Methods”, pulished online springer, 2017.
  17. Golmei Shaheamlung, Harshpreet Kaur and Mandeep Kaur, "Survey on machine learning techniques for the diagnosis of liver disease", International Conference on Intelligent Engineering and Management, IEEE, 2020.
  18. Diyar Qader Zeebaree, AdnanMohsin Abdulazeez, Dilovan Asaad Zebari, Habibollah Haron and Haza Nuzly Abdull Hamed, "Multi-Level Fusion in Ultrasound for Cancer Detection Based on Uniform LBP Features", Computers,Materials & Continua, Vol. 66, No.3, pp. 3363–3382, 2021.
  19. Diyar Qader Zeebaree, Habibollah Haron, Adnan Mohsin Abdulazeez, "Gene Selection and Classification of Microarray Data Using Convolutional Neural Network", International Conference on Advanced Science and Engineering, IEEE, 2018.
  20. Aurelien Geron, “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow”, Kiwisoft S.A.S. All rights reserved, 2019.
  21. Fahad Kamal Alsheref and Wael Hassan Gomaa, "Blood Diseases Detection using Classical Machine Learning Algorithms, International Journal of Advanced Computer Science and Applications, Vol. 10, No. 7, 2019.
  22. G. Nagarajan, A.P Mohan Raju, V. Logeshwaran, K. Nandhakumar and S. Naveenkumar, "Effective Prediction Model for Heart Disease Using Machine Learning Algorithm", International Journal of Engineering Research & Technology (I.J.E.R.T.), ISSN: 2278-0181, Special Issue – 2019.
  23. Tejaswini Untawale, "A REVIEW ON MACHINE LEARNING TECHNIQUES TO PREDICT DISEASES", International Research Journal of Modernization in Engineering Technology and Science, Vol.02, Issue: 07, July 2020.
  24. Shruti Katiyar and Shruti Jain, "Predictive Analysis on Diabetes, Liver and Kidney Diseases using Machine Learning", International Journal for Research in Applied Science & Engineering Technology (I.J.R.A.S.E.T.), ISSN: 2321-9653; I.C. Value: 45.98; S.J. Impact Factor: 7.429, Volume 8 Issue V May 2020.
  25. AJAY SHRESTHA and AUSIF MAHMOOD, "Review of Deep Learning Algorithms and Architectures", IEEE, 2019.
  26. Yuanyuan Jia, Zhiren Tan and Junxing Zhang, “DKDR: An Approach of Knowledge Graph and Deep Reinforcement Learning for Disease Diagnosis”, IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking, 2019.
  27. Meherwar Fatima and Maruf Pasha, “Survey of Machine Learning Algorithms for Disease Diagnostic”, Journal of Intelligent Learning Systems and Applications, 2017.
  28. Dildar Masood Abdulqader, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree," Technology Reports of Kansai University", ISSN: 04532198, Volume 62, Issue 03, April 2020.
  29. N.D.K.G. Dharmasiri and S. Vasanthapriyan, "Approach to Heart Diseases Diagnosis andMonitoring through Machine Learning and iOS Mobile Application", International Conference on Advances in I.C.T. for Emerging Regions, IEEE, pp. 407 – 412, 2018.
  30. Adel Al-Zebari and Abdulkadir Sengur, “Performance Comparison of Machine Learning Techniques on Diabetes Disease Detection”,IEEE, 2019.
  31. Animesh Urgiriye and Rupali Bhartiya," Review of Machine Learning Algorithm on Cancer Data Set", International Journal of Scientific Research & Engineering Trends, Volume 6, Issue 6, Nov-Dec-2020.
  32. Zoltan Geler, Vladimir Kurbalija, Mirjana Ivanovi,Milos Radovanovi, "Weighted kNN and constrained elastic distances for time-series classification", Expert Systems With Applications, Elsevier, 2020.
  33. M. SUSHMA SRI, "A Review On Object Tracking Based On K.N.N. Classifier", International Research Journal of Engineering and Technology, Vol 06, Issue: 12, December 2019.
  34. Nurul Ezzati Md Isa1, Amiza Amir, Mohd Zaizu Ilyas, and Mohammad Shahrazel Razalli, "The Performance Analysis of K-Nearest Neighbors (K-NN) Algorithm for Motor Imagery Classification Based on E.E.G. Signal, M.A.T.E.C. Web of Conferences, 2017.
  35. Rajesh N, T Maneesha, Shaik Hafeez, Hari Krishna, "Prediction of Heart Disease Using Machine Learning Algorithms", International Journal of Engineering & Technology, P 363-366, 2018.
  36. S. NagaMallik Raj, N. Thirupathi Rao, Venkata Naresh Mandhala and Debnath Bhattacharyya, "Machine Learning Algorithms To Enhance Security In Wireless Network", Journal of Critical Reviews, ISSN- 2394-5125, Vol 7, Issue 14, 2020.
  37. Diyar Qader Zeebaree, Habibollah Haron, Adnan Mohsin Abdulazeez and Subhi R. M. Zeebaree, "Combination of K-means clustering with Genetic Algorithm: A review", International Journal of Applied Engineering Research, Vol. 12, No. 24, pp. 14238-14245, 2017.
  38. Dawlat Mustafa Sulaiman, Adnan Mohsin Abdulazeez, Habibollah Haron and Shereen S. Sadiq, "Unsupervised Learning Approach-Based New Optimization K-Means Clustering for Finger Vein Image Localization", International Conference on Advanced Science and Engineering, IEEE, 2019.
  39. Alan Fuad Jahwar, Adnan Mohsin Abdulazeez, "META-HEURISTIC ALGORITHMS FOR K-MEANS CLUSTERING: A REVIEW", Palarch's Journal of Archaeology of Egypt/Egyptology, 2021.
  40. N.Valarmathy and S.Krishnaveni, "Performance Evaluation and Comparison of Clustering Algorithms used in Educational Data Mining", International Journal of Recent Technology and Engineering, ISSN: 2277-3878, Vol-7, Issue-6S5, April 2019.
  41. Susmita Ray, "A Quick Review of Machine Learning Algorithms", International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (Com-IT-Con), India, 14th -16th Feb 2019.
  42. Shraddha Shukla and Naganna S. ," A Review ON K-means DATA Clustering APPROACH", International Journal of Information & Computation Technology, Vol. 4, No. 17 , pp. 1847-1860, 2014.
  43. Adnan Mohsin Abdulazeez, Maryam Ameen Sulaiman, Diyar Qader Zeebaree, "Evaluating Data Mining Classification Methods Performance in Internet of Things Applications", Journal Of Soft Computing And Data Mining, Vol.1, NO. 2, pp. 11-25, 2020.
  44. Amani Yahyaoui, Akhtar Jamil, Jawad Rasheed, Mirsat Yesiltepe, "A Decision Support System for Diabetes Prediction Using Machine Learning and Deep Learning Techniques", IEEE, 2019.
  45. Priyanka Lodha, Ajay Talele and Kishori Degaonkar , "Diagnosis of Alzheimer's Disease using Machine Learning", IEEE, 2018.
  46. Zainuri Saringat, Aida Mustapha, R. D. Rohmat Saedudin, Noor Azah Samsudin, "Comparative analysis of classification algorithms for chronic kidney disease diagnosis", Bulletin of Electrical Engineering and Informatics, Vol. 8, No. 4, pp. 1496~1501, December 2019.
  47. Jaimin Shah and Raj Patel, "Classification techniques for Disease detection using Big-data", 4th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques, IEEE, 2019.
  48. Pavithra V and Jayalakshmi V, "Review of Feature Selection Techniques for Predicting Diseases", Proceedings of the Fifth International Conference on Communication and Electronics Systems, IEEE, 2020.
  49. Shalini M and S. Radhika, "Machine Learning techniques for Prediction from various Breast Cancer Datasets", IEEE, 2020.
  50. Ahmed Hamza Osman and Hani Moetque Aljahdali, “Diabetes Disease Diagnosis Method based on Feature Extraction using K-SVM”, International Journal of Advanced Computer Science and Applications, Vol. 8, No. 1, 2017.
  51. Aji Prasetya Wibawa and et al, Naive Bayes Classifier for Journal Quartile Classification, IJES Vol. 7, No. 2, 2019.
  52. Shahadat Uddin, Arif Khan, Md Ekramul Hossain and Mohammad Ali Moni, "Comparing different supervised machine learning algorithms for disease prediction", B.M.C. Medical Informatics and Decision Making, 2019.
  53. Raparthi Yaswanth and Y. Md. Riyazuddin, "Heart Disease Prediction using Machine Learning Techniques", International Journal of Innovative Technology and Exploring Engineering, Vol. 9, Issue-5, March 2020.
  54. Yash Jayesh Chauhan, "Cardiovascular Disease Prediction using Classification Algorithms of Machine Learning", International Journal of Science and Research (I.J.S.R.), ISSN: 2319-7064, 2018.
  55. Adel Sabry Eesa, Zeynep Orman and Adnan Mohsin Abdulazeez, "A novel feature-selection approach based on the cuttlefish optimization algorithm for intrusion detection systems", Expert Systems with Applications, Elsevier, pp. 26702679, 2015.
  56. Adel Sabry Eesa, Zeynep O.R.M.A.N., Adnan Mohsin Abdulazeez , "A new feature selection model based on ID3 and bees algorithm for intrusion detection system", Turkish Journal of Electrical Engineering & Computer Sciences, 2015.
  57. Xiaolu Tian and et al, "Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance", Hindawi Computational and Mathematical Methods in Medicine Volume, 2019.
  58. A.Deva Kumar, Josephine Prem Kumar, V.S Prakash and Divya K.S, "Supervised Learning Algorithms: A Comparison", Kristu Jayanti Journal of Computational Sciences, Vol. 1, Issue 1, pp. 01-12, 2020.
  59. Autsuo Higa, Diagnosis of Breast Cancer using Decision Tree and Artificial Neural Network Algorithms, International Journal of Computer Applications Technology and Research, Vol. 7, Issue 01, pp.23-27, 2018.
  60. S. Venkata Lakshmi, M. K. Meena and N. S. Kiruthika, "Diagnosis of Chronic Kidney Disease using Random Forest Algorithms", International Journal of Research in Engineering, Science and Management, Volume-2, Issue-3, March-2019.
  61. K.VijiyaKumar, B.Lavanya, I.Nirmala, S.Sofia Caroline, "Random Forest Algorithm for the Prediction of Diabetes", Proceeding of International Conference on Systems Computation Automation and Networking, 2019.
  62. Kaitlin Kirasich, Trace Smith and Bivin Sadler, "Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets", S.M.U. Data Science Review, Vol. 1 | No. 3, 2018.
  63. Ram MurtiRawat, Shivam Pancha, Vivek Kumar Singh and Yash Panchal, "Breast Cancer Detection Using K-Nearest Neighbors, Logistic Regression and Ensemble Learning", Proceedings of the International Conference on Electronics and Sustainable Communication Systems, IEEE, 2020.
  64. Gulshan Kumar, "A Review On Machine Learning Concept And Its Algorithms", Alochana Chakra Journal, ISSN NO: 2231-3990, 2020.
  65. Dilovan Asaad Zebari, Diyar Qader Zeebaree, Jwan Najeeb Saeed, Nechirvan Asaad Zebari, Adel AL-Zebari, Image Steganography Based on Swarm Intelligence Algorithms: A Survey, Test Engineering & Management, Vol. 83, pp. 22257 22269, 2020.
  66. Tarek M. Hassan1, Mohammed Elmogy and El-Sayed Sallam, Diagnosis of Focal Liver Diseases Based on Deep Learning Technique for Ultrasound Images, pulished onlinee, springer, 2017.
  67. Siwei Ma, Xinfeng Zhang, Chuanmin Jia, Zhenghui Zhao, Shiqi Wang, and Shanshe Wang, Image and Video Compression with Neural Networks: A Review, IEEE Transactions On Circuits And Systems For Video Technology, 2019.
  68. Mohammad Hesam Hesamian,Wenjing Jia, Xiangjian He and Paul Kennedy, Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges, Journal of Digital Imaging, Springer, 2019.
  69. Uday Pratap Singh, Siddharth Singh Chouhan, Sukirty Jain, And Sanjeev Jain, IEEE, 2019.
  70. Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami and Muhammad Khurram Khan, Medical Image Analysis using Convolutional Neural Networks: A Review, Journal of Medical Systems, 2019.
  71. Thirunavukkarasu K, Ajay S. Singh, Md Irfan and Abhishek Chowdhury, "Prediction of Liver Disease using Classification Algorithms", International Conference on Computing Communication and Automation (I.C.C.C.A.), IEEE, 2018.
  72. Utomo Pujianto, Nur A'yuni Ramadhani and Aji Prasetya Wibawa, "Support Vector Machine with Purified K-Means Clusters for Chronic Kidney Disease Detection", The 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT) 2018
  73. Naresh Khuriwal and Nidhi Mishra, "Breast Cancer Diagnosis Using Adaptive Voting Ensemble Machine Learning Algorithm", IEEE, 2018.
  74. Ankita Tyagi, Ritika Mehra and Aditya Saxena, "Interactive Thyroid Disease Prediction System Using Machine Learning Technique", 5th IEEE International Conference on Parallel, Distributed and Grid Computing(PDGC-2018), Solan, India, 20-22 Dec 2018.
  75. Priyanka Sonar and K. JayaMalini, "Diabetes Prediction Using Different Machine Learning Approaches", Proceedings of the Third International Conference on Computing Methodologies and Communication (I.C.C.M.C. 2019) IEEE, 2019.
  76. Noor Basha, Ashok Kumar P S, Gopal Krishna C and Venkatesh P, "Early Detection of Heart Syndrome Using Machine Learning Technique", 4th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT), 2019.
  77. D. Selvathi and K. Suganya, "Support Vector Machine Based Method for Automatic Detection of Diabetic Eye Disease using Thermal Images", 2019.
  78. Gokalp Cinaree and Bulent Gursel Emiroglu, "Classification of Brain Tumors by Machine Learning Algorithms", IEEE, 2019.
  79. Oumaima Terrada, Bouchaib Cherradi, Abdelhadi Raihani and Omar Bouattane, "Classification and Prediction of atherosclerosis diseases using machine learning algorithms", IEEE, 2019.
  80. Rahma Atallah and Amjed Al-Mousa, "Heart Disease Detection Using Machine Learning Majority Voting Ensemble Method", IEEE, 2019.
  81. Tahira Islam Trishna, and et al, "Detection of Hepatitis (A, B, C and E) Viruses Based on Random Forest, K-nearest and Naive Bayes Classifier", 10th I.C.C.C.N.T. 2019 July 6-8, 2019, I.I.T. Kanpur Kanpur, India, 2019.
  82. Nashat Alrefai, "Ensemble Machine Learning for Leukemia Cancer Diagnosis based on Microarray Datasets", International Journal of Applied Engineering Research ISSN 0973-4562 Volume 14, Number 21, pp. 4077-4084, 2019.
  83. J.Neelaveni and Geetha Devasana, "Alzaeimer Disease Prediction using Machine Learning Algorithm", 6th International Conference on Advanced Computing & Communication Systems (I.C.A.C.C.S.), 2020.
  84. Oyewo O.A and Boyinbode O.K, "Prediction of Prostate Cancer using Ensemble of Machine Learning Techniques", I.J.A.C.S.A.) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 3, 2020.
  85. Nikita Banerjee Subhalaxmi Das, Prediction Lung Cancer In Machine Learning Perspective, IEEE, 2020.
  86. N. Komal Kumar, G.Sarika Sindhu, D.Krishna Prashanthi, A.Shaeen Sulthana, "Analysis and Prediction of Cardio Vascular Disease using Machine Learning Classifiers", 6th International Conference on Advanced Computing & Communication Systems (I.C.A.C.C.S.), 2020.
  87. Mahzabeen Emu, Farjana Bintay Kamal, Salimur Choudhury and Thiago E. Alves de Oliveira, "Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods", IEEE, 2020.
  88. Dayanand Jamkhandikar and Neethi Priya, "Thyroid Disease Prediction Using Feature Selection And Machine Learning Classifiers", The International Journal of analytical and experimental modal analysis, ISSN NO: 0886-9367, 2020.
  89. Vidya M and Maya V Karki, "Skin Cancer Detection using Machine Learning Techniques", IEEE, 2020.
  90. Senthil Kumar Brindha and et al, "Data Mining for Early Gastric Cancer Etiological Factors from Diet-Lifestyle Characteristics", Proceedings of the International Conference on Intelligent Computing and Control Systems, IEEE, 2020.
  91. Halgurd S. Maghdid, Aras T. Asaad, Kayhan Zrar Ghafoor, Ali Safaa Sadiq and Muhammad Khurram Khan, Diagnosing COVID-19 Pneumonia from X-Ray and CT Images using Deep Learning and Transfer Learning Algorithms, arXiv preprint arXiv:2004.00038, 2020.
  92. Md. Zabirul Islam, Md. Milon Islam and Amanullah Asraf, A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images, Elsevier, 2020.

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