Baklola Mohamed, Reda Elmahdi Reem, Ali Shaimaa, Elshenawy Mohamed, Mohamed Mossad Ali, Al-Bawah Naji, Mohamed Mansour Rahma
Faculty of Medicine, Mansoura University, Mansoura, Egypt.
Faculty of Medicine, Sana'a University, Sana'a, Yemen.
Ann Med Surg (Lond). 2025 May 26;87(7):4237-4245. doi: 10.1097/MS9.0000000000003423. eCollection 2025 Jul.
Artificial intelligence (AI) is revolutionizing healthcare, particularly in disease diagnostics, by improving accuracy, efficiency, and personalization. Its applications span medical imaging, pathology, and personalized medicine, significantly enhancing patient outcomes. However, challenges such as ethical dilemmas, data privacy concerns, and algorithmic biases hinder its full integration into clinical practice. A critical gap in the literature is the lack of comprehensive frameworks for addressing these challenges, particularly in low-resource settings.
We aim to explore the current advancements, applications, and challenges of AI in disease diagnostics, emphasizing its transformative impact on healthcare systems.
A narrative review was conducted to explore the role of AI in disease diagnostics and healthcare.
AI has shown remarkable success in various domains such as medical imaging, pathology, and personalized medicine. Key technologies include machine learning, deep learning, and natural language processing, which have improved diagnostic accuracy and efficiency. Applications such as cancer detection, drug development, and wearable health monitoring devices have demonstrated a significant impact. However, challenges persist, including ethical dilemmas, algorithmic bias, regulatory gaps, and data security concerns. Innovative solutions like interdisciplinary collaboration, synthetic data generation, and robust legal frameworks are recommended to address these issues.
AI's integration into disease diagnostics has the potential to revolutionize healthcare by improving outcomes and efficiency. Nonetheless, overcoming ethical, technical, and societal challenges is critical for realizing its full potential. Continued advancements in AI, combined with responsible implementation, can transform healthcare systems and pave the way for more equitable and effective medical practices.
人工智能（AI）正在彻底改变医疗保健行业，尤其是在疾病诊断方面，它提高了准确性、效率和个性化程度。其应用涵盖医学成像、病理学和个性化医疗，显著改善了患者的治疗效果。然而，诸如伦理困境、数据隐私问题和算法偏差等挑战阻碍了它全面融入临床实践。文献中的一个关键空白是缺乏应对这些挑战的全面框架，尤其是在资源匮乏的环境中。
我们旨在探讨人工智能在疾病诊断方面的当前进展、应用和挑战，强调其对医疗系统的变革性影响。
进行了一项叙述性综述，以探讨人工智能在疾病诊断和医疗保健中的作用。
人工智能在医学成像、病理学和个性化医疗等各个领域都取得了显著成功。关键技术包括机器学习、深度学习和自然语言处理，这些技术提高了诊断的准确性和效率。癌症检测、药物开发和可穿戴健康监测设备等应用已显示出重大影响。然而，挑战依然存在，包括伦理困境、算法偏差、监管空白和数据安全问题。建议采用跨学科合作、合成数据生成和健全的法律框架等创新解决方案来解决这些问题。
人工智能融入疾病诊断有可能通过改善治疗效果和效率来彻底改变医疗保健行业。尽管如此，克服伦理、技术和社会挑战对于充分发挥其潜力至关重要。人工智能的持续进步，结合负责任的实施，可以改变医疗系统，为更公平、有效的医疗实践铺平道路。
