Malaria and Dengue Classification Using Convolutional Neural Networks:A Review

Anupama Ashok Raskar; Nikita Sanjay kolhe; Shubhangi Mahadev Moghe; Shraddha Ramakant Mumane; Mangesh Manake

Malaria and Dengue Classification Using Convolutional Neural Networks:A Review

March 2021

Vol-7, Issue-2

Paper ID: 13822

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Machine learning disease prediction malaria dengue.

Abstract

A health care facility is found to be rich in information, but not limited to information. This is because we do not have the tools and methods that are effective and efficient. By using the latest technology such as machine learning techniques and techniques and methods valuable information can be extracted from the health care system can greatly assist in further development. Malaria and Dengue are many malignant syndromes that can seriously damage the human body. We use Deep Learning algorithms to increase the accuracy of the Malaria and Dengue Diagnosis System. It acts as a desktop application where the user transmits different data such as text and image of blood cell markers. It retrieves hidden data from the database and in-depth learning model and compares user values with a set of trained data.

License

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Author Information

#	Name	Institute / Affiliation
1	Anupama Ashok Raskar	D Y Patil Institute of engineering and technology, Pune
2	Nikita Sanjay kolhe	D Y Patil Institute of engineering and technology, Pune
3	Shubhangi Mahadev Moghe	D Y Patil Institute of engineering and technology, Pune
4	Shraddha Ramakant Mumane	D Y Patil Institute of engineering and technology, Pune
5	Mangesh Manake	D Y Patil Institute of engineering and technology, Pune

How to Cite

Use the following formats to cite this article in your research.

APA Style

Raskar, Anupama Ashok, kolhe, Nikita Sanjay, Moghe, Shubhangi Mahadev, Mumane, Shraddha Ramakant, & Manake, Mangesh (2021). Malaria and Dengue Classification Using Convolutional Neural Networks:A Review. International Journal of Advance Research and Innovative Ideas In Education, 7(2), 330-336.

MLA Style

Raskar, Anupama Ashok, et al. "Malaria and Dengue Classification Using Convolutional Neural Networks:A Review." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 2, 2021, pp. 330-336.

IEEE Style

Anupama Ashok Raskar, Nikita Sanjay kolhe, Shubhangi Mahadev Moghe, Shraddha Ramakant Mumane, and Mangesh Manake, "Malaria and Dengue Classification Using Convolutional Neural Networks:A Review," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 2, pp. 330-336, 2021.

Vancouver Style

Raskar Anupama Ashok, kolhe Nikita Sanjay, Moghe Shubhangi Mahadev, Mumane Shraddha Ramakant, Manake Mangesh. Malaria and Dengue Classification Using Convolutional Neural Networks:A Review. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(2):330-336.

Harvard Style

Raskar, Anupama Ashok, kolhe, Nikita Sanjay, Moghe, Shubhangi Mahadev, Mumane, Shraddha Ramakant, & Manake, Mangesh (2021) 'Malaria and Dengue Classification Using Convolutional Neural Networks:A Review', International Journal of Advance Research and Innovative Ideas In Education, 7(2), pp. 330-336.

Chicago Style

Raskar, Anupama Ashok, et al. "Malaria and Dengue Classification Using Convolutional Neural Networks:A Review." International Journal of Advance Research and Innovative Ideas In Education 7, no. 2 (2021): 330-336.

Turabian Style

Raskar, Anupama Ashok, et al. "Malaria and Dengue Classification Using Convolutional Neural Networks:A Review." International Journal of Advance Research and Innovative Ideas In Education 7, no. 2 (2021): 330-336.