Publication

Abstract : Artificial intelligence (AI) is revolutionizing disease modelling, bringing a new era of precision and prediction to the healthcare system. By harnessing the power of big data, AI models can execute the disease dynamics, and disease progression, and even predict its outbreaks. Infectious and noninfectious diseases are challenging for individuals and society as a whole because they are associated with increasing morbidity and mortality rates. Recently, AI has emerged as a potential tool for diagnosing and managing various types of diseases. This chapter presents an overview of the state of AI applications in different types of diseases with particular emphasis on machine learning (ML), deep learning (DL), and large language model (LLM) techniques. Numerous tasks, including prognosis prediction, development of therapies, and disease diagnosis, have been addressed using the ML/DL and LLM approaches. These computational strategies have been applied to the classification and progression prediction of different types of diseases. AI has also been integrated into mobile applications to offer patients different disease therapies. Despite the promising results, several medical challenges remain to be addressed, including the need for large and diverse types of big data for training and testing those ML/DL models, as well as the need for robust and interpretable AI models. The clinical trial validation of these AI-based interventions also remains challenging. The availability of more diverse kinds of big datasets in different types of diseases further helps in advancing AI techniques and getting better medical needs of the patients and society at large. This technology has enormous potential for improving disease prevention, diagnosis, treatment, and overall patient outcomes. The present chapter deals with the different key ways AI is transforming disease modelling.