Gourisaria et al., International Journal on Emerging Technologies 11(2): 699-704(2020) 699 International Journal on Emerging Technologies 11(2): 699-704(2020) ISSN No. (Print): 0975-8364 ISSN No. (Online): 2249-3255 A Deep Learning Model for Malaria Disease Detection and Analysis using Deep Convolutional Neural Networks Mahendra Kumar Gourisaria 1 , Sujay Das 2 , Ritesh Sharma 3 , Siddharth Swarup Rautaray 4 and Manjusha Pandey 4 1 Assistant Professor, School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India. 2 B.Tech. Student, School of Electronics, KIIT Deemed to be University, Bhubaneswar, Odisha, India. 3 B.Tech. Student, School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India. 4 Associate Professor, School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India. (Corresponding author: Mahendra Kumar Gourisaria) (Received 04 January 2020, Revised 10 March 2020, Accepted 12 March 2020) (Published by Research Trend, Website: www.researchtrend.net) ABSTRACT: Malaria is a very infectious disease that is caused by female anopheles mosquito. This disease not only harms humans but also animals. If this disease not diagnosed properly in the early stage than it can cause muscular paralysis or even death of the patient in worst case. Due to lack of highly technical expertise in industry, it becomes very difficult to confirm the presence of disease. In this context, the intervention of IT must be involved for proper and rapid detection of disease. Modern day IT sectors are putting their blood and sweat for fighting this disease by taking the help of IT sector buzz words technologies like Machine Learning, Deep Learning and Artificial Intelligence. These technologies have been a backbone for healthcare since the last few years and will continue to be if used properly. This paper uses the CNN algorithm on the microscopic image of the malaria infected blood cells to predict if an organism is suffering from malaria or not. Our proposed model got accuracy of 95.23% and out of 16 random images, 15 are always predicted correctly. Keywords: Deep Convolutional Neural Network, Image Processing, Malaria Detection, Artificial Neural Network, Deep Learning, Medical Imaging, Disease Detection. I. INTRODUCTION Improvement in the system of healthcare is the need of the hour. Using AI in the field of healthcare can solve the problems associated in the field of healthcare up to some extent. Artificial Intelligence is a sophisticated technique which uses complex algorithms to emulate human like behavior in case of the analysis of complex data. It also has the interesting ability to predict without the interference of any direct human contact. The reason is that makes AI technology better than obsolete technologies in the field of medical and healthcare are its power to acquire information, take action and give correct output to the user. Artificial Intelligence does this by the use of various Machine Learning and Deep Learning algorithm [1]. The father and the founding member of modern computer and AI is Sir Alan Turning. The year which saw an increase in the amount of interest in the technique of AI was 1980s and 1990s. The complex techniques like Fuzzy expert systems, Bayesian Networks, ANN were used in healthcare systems. In the year 2016 people all over the world saw a huge amount of investments that were in the field of healthcare as compared to the other sectors. AI in medical can be useful in many ways like in virtual section, use of neural network to develop a model which can recognize brain tumor and in physical part and help robots to perform surgery. AI is whooshing its way into the public sector. It can help physicians to identify which patient will require more attention. By doing this the doctor can provide personalized rules and regulation for treatment for each individual. Artificial Intelligence can be used by primary care physicians for preparing their records, study their discourse with patients and feed the relevant information to EHR systems directly. These AI driven systems helps to gather the patient data and then analyze it and present it to physicians to get analysis of medical needs of patients [2]. AI has a very vast application in the case of medicine and healthcare. It can be used to detect disease like malaria, tumors and can also provide personalized medical care. For a person it can become a very tedious work to correctly classify a disease. Here AI plays an important role, as it can perform these tasks with ease. It can be used to detect lung cancer or heart strokes based on CT scan. AI proves to be very helpful to classify skin cancer based on skin images. Developing an AI product which detects a disease takes very less amount of time in comparison with a doctor. Similarly developing a drug is a very notorious and very costly process. It can take many years of hard work and it has the potential to shave off years of hard work. If it fails then it can result in the loss of millions of dollars. AI can similarly be used to design drugs. The other application of AI in medical are providing personalized treatments and improving gene editing [3]. Use of AI in the field of health care can transform the field magically. It can create wonders. There has been quite a few works in AI like detecting lung cancer, pneumonia and other diseases. AI proves itself more accurate and faster at diagnosis than real life doctors [4]. Malaria is the disease which can prove very fatal for the organism if not diagnosed in early stages and is caused by parasites. It can be transmitted to people if bitten by the female anopheles mosquitoes. This disease can be completely prevented and cured provided precautions must be taken well before the matter gets out of our e t