Artificial Intelligence in Post Pandemic Healthcare

EasyChair Preprint no. 13489

Abstract

One of the most historical and devastating phenomena in the current century was Covid 19 pandemic. A major part of the world population was infected due to the sudden outbreak and claimed many lives. The pandemic impacts almost every aspects of the world infrastructure. The major hit back is observed in the healthcare sector. To combat the virus outbreak, artificial intelligence is emerged to be an innovative strategy. AI mimics the human mind which can thinks like a human mind and have the complex problem-solving ability with much less time compared to human mind. At the time of pandemic, Machine Learning (ML) and Deep Learning (DL) algorithms along with AI innovations is countered to combat the outbreak. Supervised ML techniques such as tree-based models (random forest, gradient boosted trees), support vector machine models, K- nearest neighbor algorithms are extensively used. The amalgamation of Artificial Intelligence (AI) and Internet of Things (IoT) termed as AI-IoT is used for the containment of the disease.AI-IoT helps by forecasting the pandemic progress, real time data analysis, contact tracing, remediation control, estimation of the number of cases and death rate, workload reduction of healthcare workers, drug discovery and development etc. In the postpandemic era, due to digitalization and AI can strengthen and properly maintain the healthcare sector. Using AI, limited healthcare resources can be managed, personalized patient management and treatment plans can be done.AI-based techniques can also diagnose, prevent, and treat cancer, hypertension, diabetes, and other communicable diseases.AI-based algorithms can improve telepharmacy and reduce healthcare worker stress. Moreover, AI-based strategies can be useful for the diagnosis, prevention, and management of diseases such as cancer, hypertension, diabetes, and other communicable diseases. Adopting AI-based algorithms can improve the telepharmacy sector and reduce the burden on healthcare workers.

Keyphrases: Algorithms, COVID-19, Internet of Things (IoT), machine learning, telepharmacy

@Booklet{EasyChair:13489,
  author = {Sarad Pawar Naik Bukke and Chandrakala Venkatesh and Anupam Maity and Chandrashekar Thalluri and Narayana Goruntla and Mekuriya Yadesa Tadele and John Soosamma},
  title = {Artificial Intelligence in Post Pandemic Healthcare},
  howpublished = {EasyChair Preprint no. 13489},

  year = {EasyChair, 2024}}