International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 11, No. 5, 8 Oct. 2021
Cover page and Table of Contents: PDF (size: 563KB)
Machine Learning and Artificial Intelligence Based Identification of Risk Factors and Incidence of Gastroesophageal Reflux Disease in Pakistan
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Author(s)
Index Terms
Gastroesophageal reflux disease, GERD, Pakistan, risk factors, prevalence, artificial intelligence, machine learning
Abstract
The disease burden of Gastroesophageal Reflux Disease (GERD) varies across the globe and have a significant impact on the overall health of the communities. A number of complications and diseases stem from chronic GERD. In order to provide improved healthcare measures and to effectively monitor and control GERD, it is important to identify rate of incidence of the disease and the associated risk factors along with symptoms. Therefore, this study was conducted by retrieving the relevant data through machine learning. Principles of Artificial Neural Networks were applied to sort the data and the results were obtained in the form of a network by using VOSviewer software. These artificial intelligence and machine learning based results reveal that the Asian population is increasingly becoming prone to GERD and sporadic reports from Pakistan have surmounted to disclose that GERD is constantly present across different districts and cities of Pakistan. The major risk factors identified among the Pakistani population in different research articles include consumption of oily foods, the habit of having late dinners, sedentary lifestyles and a lack of understanding about disease diagnosis, and GERD management and treatment. Our results suggest that acid reflux and inflammation of esophageal cavity are some of the main symptoms of the disease. On the basis of the results obtained, it is speculated that this study will provide a ground to improve the symptomatic diagnosis of GERD by closely observing and analyzing the risk factors and the rate of incidence with symptoms. It would enable the healthcare facilities to effectively monitor the GERD cases so that the disease burden due to GERD and related illnesses could be reduced. Moreover, the identification of regional differences and a comparative data would help us in identifying the disease hotspots where more efforts would be needed to manage and control the disease.
Cite This Paper
Mustafa Kamal Pasha, " Machine Learning and Artificial Intelligence Based Identification of Risk Factors and Incidence of Gastroesophageal Reflux Disease in Pakistan", International Journal of Education and Management Engineering (IJEME), Vol.11, No.5, pp. 23-31, 2021. DOI: 10.5815/ijeme.2021.05.03
Reference
[1]Ahmed, R., Rizwan-ur-Rashid, M. P., & Ahmed, S. W. Prevalence of cigarette smoking among young adults in Pakistan. J Pak Med Assoc, 2008,. 58(11), 597-601.
[2]Argyrou, A., Legaki, E., Koutserimpas, C., Gazouli, M., Papaconstantinou, I., Gkiokas, G., & Karamanolis, G. Risk factors for gastroesophageal reflux disease and analysis of genetic contributors. World journal of clinical cases, 2018, 6(8), 176.
[3]Fujiwara, Y., Machida, A., Watanabe, Y., Shiba, M., Tominaga, K., Watanabe, T. & Arakawa, T. Association between dinner-to-bed time and gastro-esophageal reflux disease. The American journal of gastroenterology, 2005, 100(12), 2633.
[4]Furuta, T., Sugimoto, M., Kodaira, C., Nishino, M., Yamade, M., Ikuma, M. & Hishida, A.. CYP2C19 genotype is associated with symptomatic recurrence of GERD during maintenance therapy with low-dose lansoprazole. European journal of clinical pharmacology, 2009, 65(7), 693-698.
[5]Herbella, F. A., & Patti, M. G. Gastroesophageal reflux disease: From pathophysiology to treatment. World journal of gastroenterology: WJG, 2010, 16(30), 3745.
[6]Iwakiri, K., Kinoshita, Y., Habu, Y., Oshima, T., Manabe, N., Fujiwara, Y. & Ashida, K. Evidence-based clinical practice guidelines for gastroesophageal reflux disease 2015. Journal of gastroenterology, 2016, 51(8), 751-767.
[7]Jafri, N., Jafri, W., Yakoob, J., Islam, M., Manzoor, S., Jalil, A., & Hashmi, F.. Perception of gastroesophageal reflux disease in urban population in Pakistan. Journal of the College of Physicians and Surgeons--Pakistan: JCPSP, 2005, 15(9), 532-534.
[8]Jung, H. K. Epidemiology of gastroesophageal reflux disease in Asia: a systematic review. Journal of neurogastroenterology and motility, 2011, 17(1), 14.
[9]Karim, S., Jafri, W., Faryal, A., Majid, S., Salih, M., Jafri, F. & Tariq, U. Regular post dinner walk; can be a useful lifestyle modification for gastroesophageal reflux. Journal of the Pakistan Medical Association, 2011, 61(6), 526.
[10]Khan, H. N., Suleman, A., Ullah, R., Abdullah, A., & Naz, S. GASTRO ESOPHAGEAL REFLUX DISEASES IN CHRONIC OBSTRUCTIVE PULMONARY DISEASE PATIENTS. Journal of Ayub Medical College Abbottabad, 2017, 30(1), 64-66.
[11]Mao, W. M., Zheng, W. H., & Ling, Z. Q. Epidemiologic risk factors for esophageal cancer development. Asian Pac J Cancer Prev, 2011, 12(10), 2461-2466.
[12]Menezes, M. A., & Herbella, F. A. Pathophysiology of gastroesophageal reflux disease. World journal of surgery, 2017, 41(7), 1666-1671.
[13]Munawar HS, Hammad A, Ullah F, Ali TH. After the flood: A novel application of image processing and machine learning for post-flood disaster management. InProceedings of the 2nd International Conference on Sustainable Development in Civil Engineering (ICSDC 2019), Jamshoro Pakistan 2019a Dec (pp. 5-7).
[14]Munawar, H. S. An Overview of Reconfigurable Antennas for Wireless Body Area Networks and Possible Future Prospects. International Journal of Wireless and Microwave Technologies (IJWMT);2020, 10(4), 1-8.
[15]Munawar, H. S. Applications of Leaky-wave Antennas: A Review. International Journal of Wireless and Microwave Technologies (IJWMT); 2020, 10(4), 56-62.
[16]Munawar, H. S. Reconfigurable Origami Antennas: A Review of the Existing Technology and its Future Prospects. International Journal of Wireless and Microwave Technologies (IJWMT); 2020, 4, 34-38.
[17]Munawar, H. S., & Maqsood, A., Mustansar, Z. Isotropic Surround Suppression based Linear Target Detection using Hough Transform. International Journal of Advanced And Applied Sciences; 2017, 4(8), 37-42.
[18]Munawar, H. S., Khalid, U., Jilani, R., & Maqsood, A. (2017). Version Management by Time Based Approach in Modern Era. International Journal of Education and Management Engineering, 4, 13-20.
[19]Munawar, H. S., Qayyum, S., Ullah, F., & Sepasgozar, S. Big Data and Its Applications in Smart Real Estate and the Disaster Management Life Cycle: A Systematic Analysis. Big Data and Cognitive Computing; 2020, 4(2).
[20]Munawar, H. S., Zhang, J., Li, H., Mo, D., & Chang, L. Mining multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 189-200). Springer, Cham. . (2019b, April)
[21]Munawar, H. S., Khalid, U., & Maqsood, A. Fire detection through Image Processing; A brief overview.
[22]Munawar, H. S., Khalid, U., & Maqsood, A. Modern day detection of Mines; Using the Vehicle Based
[23]Detection Robot. Munawar HS, Awan AA, Maqsood A, Khalid U. REINVENTING RADIOLOGY IN MODERN ERA.
[24]Munawar, H. S. Flood Disaster Management: Risks, Technologies, and Future Directions. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 2020, 1, 115-146.
[25]Munawar, H. S. Image and Video Processing for Defect Detection in Key Infrastructure. Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies and Applications, 2020, 1, 159-177.
[26]Nadaleto, B. F., Herbella, F. A., & Patti, M. G.. Gastroesophageal reflux disease in the obese: Pathophysiology and treatment. Surgery, 2016, 159(2), 475-486.
[27]Shaukat, F., Jawaid, M., Rizwan, A., & Kumar, B. Primary-care physicians' perceptions and practices regarding History of Gastro Esophageal Reflux Disease: a national survey. Rawal Medical Journal, 2018, 43(4), 764-766.
[28]Vaezi, M. F., Pandolfino, J. E., Vela, M. F., & Shaheen, N. J.. White paper AGA: Optimal strategies to define and diagnose gastroesophageal reflux disease. Clinical Gastroenterology and Hepatology, 2017, 15(8), 1162-1172.
[29]Veugelers, P. J., Porter, G. A., Guernsey, D. L., & Casson, A. G. Obesity and lifestyle risk factors for gastroesophageal reflux disease, Barrett esophagus and esophageal adenocarcinoma. Diseases of the Esophagus, 2006, 19(5), 321-328.
[30]Zaman, H., Zeb, J., Farooq, M. U., Shah, M. T., Qayyum, S. W., & Abbasi, M. A. SOCIO-DEMOGRAPHIC CHARACTERISTICS OF GASTROESOPHAGEAL REFLUX DISEASE PATIENTS. Pakistan Journal of Physiology, 2016, 12(3), 40-43.