A Comprehensive Review of Artificial Intelligence in Healthcare: Emphasizing the Need for Explainability in Patient-Centric Applications

Artificial intelligence (AI) has seen an extensive boom in all fields, including media, commerce, technology, and healthcare.In spite of this proliferation, its predictions and analysis still create a sense of distrust among those who must use these results, particularly in critical fields such as healthcare, national security, and complex domains such as law and order.These black-box models generate trust issues among users.Explainable artificial intelligence has emerged as a set of methods and processes that allows users to understand and trust the results of AI models.This study focuses on how explainable artificial intelligence can provide transparent, interpretable, and reliable decision-making processes, making it a compelling alternative to traditional AI models in the healthcare industry.Additionally, a comprehensive review of the various applications of artificial intelligence in the medical field is presented for diagnosing complex diseases such as cancer, neurological problems, medical diagnoses, and pathology.This analysis, combined with the practical knowledge of clinical professionals, can significantly impact the functioning of our traditional healthcare system and prove to be a transformative, patient-centered approach to healthcare delivery.