Abstract

Deep learning has received much interest in the field of healthcare in recent years. Health care plays a significant role in delivering services and practices that promote, maintain, and restore health of an individual. However, applying deep learning in healthcare is still an exciting area of research. This paper explores the application of deep learning, and henceforth, it highlights new perspectives in healthcare by reviewing published state-of-the-art research works from four scholarly databases, including Scopus, Web of Science, Pubmed, and Google Scholar. The selected studies were from April 2014 to April 2024, and based on the predefined quality assessment criteria, 16 articles were thoroughly reviewed after the preliminary extraction, review, and screening phases. The study’s findings indicate that deep learning has been applied in healthcare, particularly in medical images, digital consultation, Electronic medical records, and genomics. Furthermore, challenges such as deep learning cannot replicate the human touch and emotional connection that patients often seek in their healthcare journey, and data privacy are highlighted. Lastly, new perspectives, such as leveraging emerging technologies like Augmented Reality (AR), Virtual Reality (VR), and federated learning, are suggested to address these challenges

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