Analysis of Psycological and Physical Impact on Individuals During Covid-19 Through Machine Learning Technique

EasyChair Preprint 7335

Abstract

Adoption of machine learning and data mining in health care is to minimize errors in predicting disease, prescription of medicines, perception of individuals, and detection of diseases in its early stage. The proposed research aims to develop an intelligent decision making model that shall aid in revising medical pedagogies and remedial instructions and precaution and guidelines for human beings identified with low immunity and weak body strength, well before they face major clinical problem. This model shall also recognize the behaviour of patient and on the basis of their behavioural symptom we can predict who is most vulnerable to disease or at low risk. We will also try to find out post COVID-19 effects on patients and psychological impact of any pandemic on their lifestyle. This paper is an extensive coverage of integration of algorithms and logic with various data mining and machine learning techniques to handle healthcare and uncertainty at various levels to incorporate human type reasoning in modelling. Naive Bayes, K. Nearest neighbor and many more techniques can be used for Classifying people. We are planning to collect data set with different clinical and non-clinical behaviours. It involves a combination of techniques from numerous domains such as machine learning, organizing databases and information retrieval.

Keyphrases: Clustering, Co-relation Analysis, Data Mining, Naïve Bayes, machine learning

@booklet{EasyChair:7335,
  author    = {Nisha Bhoi},
  title     = {Analysis of Psycological and Physical Impact on Individuals During Covid-19 Through Machine Learning Technique},
  howpublished = {EasyChair Preprint 7335},
  year      = {EasyChair, 2022}}