https://stm2.bookpi.org/AITHDIEI <p>The advent of Artificial Intelligence (AI) represents one of the most transformative developments in modern science and technology. Its integration into the healthcare domain is revolutionising how diseases are diagnosed, monitored, and treated, enhancing clinical accuracy and operational efficiency. This academic work, <strong>“</strong><em>Artificial Intelligence Technologies for Healthcare Diagnosis and Intervention “</em>, has been undertaken with the aim of exploring the breadth and depth of AI applications across various branches of medicine.</p> <p>This text serves as a comprehensive resource for students, researchers, and practitioners in the fields of healthcare, biomedical engineering, computer science, and health informatics. It begins with a foundational overview of AI’s emergence in healthcare, tracing its historical roots and contextualising its current trajectory. The subsequent chapters delve into specific areas where AI is making significant strides, particularly in medical imaging, predictive analytics, personalised medicine, and surgical robotics.</p> <p>Special attention is given to the technical underpinnings of AI, including the role of convolutional neural networks (CNNs) in image analysis, the utilisation of electronic health records (EHRs) for predictive modelling, and the convergence of genomics with machine learning for individualised treatment planning. The work also critically addresses ethical and regulatory challenges, such as data privacy, algorithmic fairness, and accountability, issues that must be navigated carefully to ensure safe and equitable AI integration.</p> <p>Looking forward, the final chapters project the future of AI in medicine, highlighting promising directions such as explainable AI (XAI), federated learning, and human-AI collaboration. The goal is not only to document the current state of the field but also to inspire further inquiry and innovation, ensuring that AI technologies are harnessed responsibly for the benefit of patients and healthcare systems globally.</p> <p>This compilation reflects interdisciplinary scholarship and practical insights, drawn from both peer-reviewed literature and real-world implementations. It is hoped that this work will contribute meaningfully to the ongoing dialogue on the ethical, scientific, and societal implications of AI in healthcare.</p> en-US Artificial Intelligence Technologies in Healthcare: Diagnosis, Intervention and Ethical Integration https://stm2.bookpi.org/AITHDIEI/article/view/103 <p>The rapid advancement of Artificial Intelligence (AI) technologies has initiated a paradigm shift in healthcare, particularly in the realms of medical diagnosis and treatment. This study provides a comprehensive academic examination of how AI, through subfields such as machine learning, deep learning, and natural language processing, is revolutionising clinical decision-making, diagnostic precision, and individualised patient care. The work systematically explores AI's integration into key healthcare domains, including medical imaging, predictive analytics, personalised medicine, and robotic surgery. Specific attention is given to the application of convolutional neural networks (CNNs) in radiology, pathology, and dermatology, where AI systems now rival human experts in diagnostic accuracy.</p> <p>Furthermore, this research highlights the predictive power of AI in identifying the onset of chronic and neurodegenerative diseases by leveraging electronic health records (EHRs), genomic data, and wearable technologies. In personalised medicine, AI facilitates pharmacogenomic profiling and individualised oncology treatment strategies. The integration of AI in surgical robotics is also examined, emphasising improvements in intraoperative precision and post-operative monitoring.</p> <p>While the potential of AI is vast, the study also addresses significant challenges, including data privacy, algorithmic bias, lack of transparency, and regulatory hurdles. Ethical and legal considerations are critically analyzed, underscoring the need for fair, interpretable, and accountable AI systems. The final chapters focus on future directions, such as multimodal data integration, explainable AI (XAI), federated learning, and human-AI collaboration, which are poised to shape the next generation of healthcare solutions.</p> <p>This research concludes with policy recommendations and strategic priorities to guide responsible AI deployment in clinical environments, advocating for interdisciplinary collaboration and robust governance frameworks. The findings underscore AI’s transformative potential in medicine, while emphasizing the importance of ethical oversight and equity in technological advancement.</p> Dr. Rooth Vasantha Medapati Dr. V.Raja Babu Prof. Saritha Medapati Dr. D.Udaya Kumar Copyright (c) 2025 Author(s). The licensee is the publisher (BP International). 2025-07-05 2025-07-05 1 57 10.9734/bpi/mono/978-81-989371-9-3