Explainable artificial intelligence (EAI)
Amreen Ayesha, N. Nasurudeen Ahamed · 2024
Explainable artificial intelligence (EAI) has emerged as a critical paradigm in the field of healthcare, offering unprecedented opportunities for enhancing patient care, diagnostic accuracy, and treatment outcomes. This abstract provides a concise overview of the significance and implications of EAI in healthcare applications and its potential to drive substantial improvements in the industry. In recent years, the integration of AI and machine learning techniques into healthcare systems has led to groundbreaking advancements in disease prediction, medical image analysis, drug discovery, and treatment personalization. However, the inherent opacity and complexity of many AI models have raised concerns regarding their trustworthiness and accountability in critical healthcare decisions. EAI addresses these concerns by providing transparent and interpretable AI models that not only deliver accurate predictions but also offer insights into the underlying decision-making processes. Here we discuss the multifaceted benefits of EAI in healthcare, including its ability to improve clinical decision support systems, enhance patient–doctor communication, and facilitate regulatory compliance. Furthermore, it explores various techniques and approaches employed in EAI, such as rule-based systems, feature importance analysis, and model-agnostic interpretability methods. These techniques empower healthcare professionals to understand AI-driven recommendations, validate their clinical relevance, and make informed decisions that align with the best interests of patients. The overview also sheds light on the challenges and future prospects of EAI in healthcare, emphasizing the need for standardized frameworks, data privacy safeguards, and continuous research to refine and expand the field. As the healthcare industry continues to harness the potential of AI, the adoption of EAI promises to bridge the gap between advanced technology and human expertise, ultimately leading to more effective, transparent, and accountable healthcare solutions. This abstract serves as an introduction to the pivotal role that explainable artificial intelligence plays in shaping the future of healthcare and highlights its potential to revolutionize patient care and medical research.