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Review
. 2025 Dec;11(1):2527505.
doi: 10.1080/20565623.2025.2527505. Epub 2025 Jul 4.

Integrating artificial intelligence in healthcare: applications, challenges, and future directions

Peng Lean Chong  1 , Vikneswaran Vaigeshwari  1 , Basir Khan Mohammed Reyasudin  2 , Binti Ros Azamin Noor Hidayah  1 , Purnshatman Tatchanaamoorti  1 , Jian Ai Yeow  3 , Feng Yuan Kong  4
Affiliations
Review

Integrating artificial intelligence in healthcare: applications, challenges, and future directions

Peng Lean Chong et al. Future Sci OA. 2025 Dec.

Abstract

Artificial intelligence (AI) has demonstrated remarkable potential in transforming medical diagnostics across various healthcare domains. This paper explores AI applications in cancer detection, dental medicine, brain tumor database management, and personalized treatment planning. AI technologies such as machine learning and deep learning have enhanced diagnostic accuracy, improved data management, and facilitated personalized treatment strategies. In cancer detection, AI-driven imaging analysis aids in early diagnosis and precise treatment decisions. In dental healthcare, AI applications improve oral disease detection, treatment planning, and workflow efficiency. AI-powered brain tumor databases streamline medical data management, enhancing diagnostic precision and research outcomes. Personalized treatment planning benefits from AI algorithms that analyze genetic, clinical, and lifestyle data to recommend tailored interventions. Despite these advancements, AI integration faces challenges related to data privacy, algorithm bias, and regulatory concerns. Addressing these issues requires improved data governance, ethical frameworks, and interdisciplinary collaboration among healthcare professionals, researchers, and policymakers. Through comprehensive validation, educational initiatives, and standardized protocols, AI adoption in healthcare can enhance patient outcomes and optimize clinical decision-making, advancing the future of precision medicine and personalized care.

Keywords: Artificial intelligence; brain tumour databases; cancer detection; dental healthcare; personalized treatment planning.

Plain language summary

This article explores how artificial intelligence (AI) is being used to improve healthcare. AI can analyze large amounts of data quickly, helping doctors detect diseases earlier, plan treatments more accurately, and manage patient records more efficiently. It is particularly useful in cancer diagnosis, dental health, brain tumor analysis, and personalized treatment planning. For example, AI tools can examine medical images to spot tumors or oral issues that may be missed by the human eye, and machine learning algorithms can suggest treatment options based on a patient’s unique history and health data. The study highlights successful applications of AI, such as using advanced image recognition to identify cancer, optimizing dental procedures, and improving brain tumor classification. Despite these benefits, challenges remain. These include concerns over data privacy, the fairness and transparency of AI decisions, the need for high-quality training data, and ensuring that medical professionals are trained to use AI effectively. The authors recommend stronger ethical guidelines, better education for healthcare workers, and improved validation of AI systems. With ongoing research and careful integration, AI has the potential to make healthcare more precise, efficient, and personalized, ultimately improving outcomes for patients and supporting doctors in delivering high-quality care.

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Conflict of interest statement

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Figures

Figure 1.
Figure 1.
Primary uses of artificial intelligence (AI) in the healthcare industry. This schematic illustrates the key applications of AI technologies within healthcare, including cancer detection, dental healthcare, brain tumor database management, and personalized treatment planning. Each application is highlighted with a representative icon and brief description to demonstrate the diversity of AI implementations across diagnostic, treatment, and data management functions.
See this image and copyright information in PMC

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