Litcius/Paper detail

Towards Applicability of Information Communication Technologies in Automated Disease Detection

Abu Sarwar Zamani, Seema Rajput, Harjeet Kaur, Dr.V.Harishnath Dr.A.Meenakshi, Sunil L. Bangare, Samrat Ray

2022INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING12 citationsDOIOpen Access PDF

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.

Topics & Concepts

Computer sciencePreprocessorProcess (computing)Artificial intelligenceVariety (cybernetics)Machine learningSupport vector machineData pre-processingMedical diagnosisData scienceMedicineOperating systemPathologyCOVID-19 diagnosis using AIArtificial Intelligence in HealthcareAnomaly Detection Techniques and Applications
Towards Applicability of Information Communication Technologies in Automated Disease Detection | Litcius