A Review on Indian State/City Covid-19 Cases Outbreak Forecast utilizing Machine Learning Models

Abstract

S everal scene supposition models for COVID-19 are "be ing utilized by experts around the globe to settle on trained choices and keep up fitting control measures. Man-made awareness Machine Learning (ML) based choosing fragments have shown their significance to foresee perioperative results to improve the dynamic of things to come course of activities. The ML models have been utilized in different application spaces which required the obvious check and prioritization of undesirable parts for a danger. A few supposition techniques are in fact unavoidably used to oversee imagining issues. This evaluation shows the limitation of Machine Learning models to ascertain the amount of moving toward patients influenced by COVID-19 which is considered as a typical risk to humanity. S pecifically, four standard choosing models, for example, Linear apostatize, keep up vector machine, MLP, Decision Tree, Boosted Random Forest, Regression Tree, and Extra Tree have been utilized in this evaluation to figure the compromising elements of COVID-19. Three kinds of guesses are made by the aggregate of the models, for example, the number of starting late polluted cases after and before starter vexing, the number of passing's after and before groundwork vexing, and the number of recuperation after and before groundwork vexing. The outcomes made by the evaluation display a promising structure to utilize these systems for the" current situation of the COVID-19 pandemic.

On‐Ground Distributed COVID‐19 Variant Intelligent Data Analytics for a Regional Territory

“…If the value of R 2 is deduced to be 1, it denotes that the regression predictions accurately align with the data. Thus, the closer the value of R 2 is to 1, the more influential the model is in predicting trends [19]. The random forest algorithm is a popular unsupervised machine learning algorithm, and it is employed for classification [20,21].…”

“…Upon obtaining the samples and analyzing the virus genetics, it was established that it caused the outbreak. The virus was named Coronavirus 2019 (COVID- 19) by the WHO in February 2020 [7], while some studies found that this deadly COVID-19 virus is associated with SARS-CoV-2 [8,9]. With its 204 million population, Pakistan saw first of its case in February 2020 [10].…”

A Review on Machine Learning and Deep Learning Methods on Medical Image Classification

“…Agarwal et al [1] describe the use of machine learning models to enhance diagnostic accuracy for thyroid diseases, while Chakraborty et al [2] leverage BERTpowered models to detect AI-generated content, highlighting advancements in preserving textual authenticity. Degadwala et al [3] employ machine learning regression techniques to forecast cholera patterns, aiming for precise and actionable disease prediction.…”