Towards Applicability of Information Communication Technologies in Automated Disease Detection
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Abstract
The classification and diagnosis of a wide variety of diseases may now be performed in an accurate and efficient manner because to advancements in information and communication technologies. According to the conclusions of this enormous body of research, data mining and machine learning (ML) technologies have the potential to be used in the process of discovering and diagnosing disorders. Before we can make this technology available to the medical community, we need to first overcome the limits of data mining and machine learning technologies so that we can get a comprehensive understanding of this dangerous virus. Image processing and support vector machines, both of which are extensively covered during the course of this work, constitute the foundation of our method for the classification and detection of disorders. The CLAHE approach is used for image preprocessing, while the K means algorithm is utilised for picture segmentation.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Zamani, A. S., Dr. Seema H. Rajput, Dr. Harjeet Kaur, Dr.Meenakshi, Dr. Sunil L. Bangare, & Samrat Ray. (2022). Towards Applicability of Information Communication Technologies in Automated Disease Detection. International Journal of Next-Generation Computing, 13(3). https://doi.org/10.47164/ijngc.v13i3.705
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