Infectious Disease Forecasting in India using LLM's and Deep Learning

• URL: http://arxiv.org/abs/2410.20168v1
• Date: Sat, 26 Oct 2024 12:54:09 GMT
• Title: Infectious Disease Forecasting in India using LLM's and Deep Learning
• Authors: Chaitya Shah, Kashish Gandhi, Javal Shah, Kreena Shah, Nilesh Patil, Kiran Bhowmick,
• Abstract summary: This paper implements deep learning algorithms and LLM's to predict the severity of infectious disease outbreaks. The insights from our research aim to assist in creating a robust predictive system for any outbreaks in the future.
• Score: 0.3141085922386211
• License:
• Abstract: Many uncontrollable disease outbreaks of the past exposed several vulnerabilities in the healthcare systems worldwide. While advancements in technology assisted in the rapid creation of the vaccinations, there needs to be a pressing focus on the prevention and prediction of such massive outbreaks. Early detection and intervention of an outbreak can drastically reduce its impact on public health while also making the healthcare system more resilient. The complexity of disease transmission dynamics, influence of various directly and indirectly related factors and limitations of traditional approaches are the main bottlenecks in taking preventive actions. Specifically, this paper implements deep learning algorithms and LLM's to predict the severity of infectious disease outbreaks. Utilizing the historic data of several diseases that have spread in India and the climatic data spanning the past decade, the insights from our research aim to assist in creating a robust predictive system for any outbreaks in the future.

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