Iqbal Javed, Cortés Jaimes Diana Carolina, Makineni Pallavi, Subramani Sachin, Hemaida Sarah, Thugu Thanmai Reddy, Butt Amna Naveed, Sikto Jarin Tasnim, Kaur Pareena, Lak Muhammad Ali, Augustine Monisha, Shahzad Roheen, Arain Mustafa
Neurosurgery, Mayo Hospital, Lahore, PAK.
Epidemiology, Universidad Autónoma de Bucaramanga, Bucaramanga, COL.
Cureus. 2023 Sep 4;15(9):e44658. doi: 10.7759/cureus.44658. eCollection 2023 Sep.
Artificial intelligence (AI) has opened new medical avenues and revolutionized diagnostic and therapeutic practices, allowing healthcare providers to overcome significant challenges associated with cost, disease management, accessibility, and treatment optimization. Prominent AI technologies such as machine learning (ML) and deep learning (DL) have immensely influenced diagnostics, patient monitoring, novel pharmaceutical discoveries, drug development, and telemedicine. Significant innovations and improvements in disease identification and early intervention have been made using AI-generated algorithms for clinical decision support systems and disease prediction models. AI has remarkably impacted clinical drug trials by amplifying research into drug efficacy, adverse events, and candidate molecular design. AI's precision and analysis regarding patients' genetic, environmental, and lifestyle factors have led to individualized treatment strategies. During the COVID-19 pandemic, AI-assisted telemedicine set a precedent for remote healthcare delivery and patient follow-up. Moreover, AI-generated applications and wearable devices have allowed ambulatory monitoring of vital signs. However, apart from being immensely transformative, AI's contribution to healthcare is subject to ethical and regulatory concerns. AI-backed data protection and algorithm transparency should be strictly adherent to ethical principles. Vigorous governance frameworks should be in place before incorporating AI in mental health interventions through AI-operated chatbots, medical education enhancements, and virtual reality-based training. The role of AI in medical decision-making has certain limitations, necessitating the importance of hands-on experience. Therefore, reaching an optimal balance between AI's capabilities and ethical considerations to ensure impartial and neutral performance in healthcare applications is crucial. This narrative review focuses on AI's impact on healthcare and the importance of ethical and balanced incorporation to make use of its full potential.
人工智能（AI）开辟了新的医学途径，彻底改变了诊断和治疗方法，使医疗服务提供者能够克服与成本、疾病管理、可及性和治疗优化相关的重大挑战。机器学习（ML）和深度学习（DL）等著名的人工智能技术对诊断、患者监测、新型药物发现、药物开发和远程医疗产生了巨大影响。利用人工智能生成的算法用于临床决策支持系统和疾病预测模型，在疾病识别和早期干预方面取得了重大创新和改进。人工智能通过加强对药物疗效、不良事件和候选分子设计的研究，对临床药物试验产生了显著影响。人工智能在患者基因、环境和生活方式因素方面的精准度和分析能力带来了个性化治疗策略。在新冠疫情期间，人工智能辅助的远程医疗为远程医疗服务和患者随访树立了先例。此外，人工智能生成的应用程序和可穿戴设备实现了对生命体征的动态监测。然而，除了具有巨大变革性之外，人工智能对医疗保健的贡献也受到伦理和监管方面的关注。人工智能支持的数据保护和算法透明度应严格遵循伦理原则。在通过人工智能驱动的聊天机器人、医学教育强化和虚拟现实培训将人工智能纳入心理健康干预之前，应建立强有力的治理框架。人工智能在医疗决策中的作用存在一定局限性，这凸显了实践经验的重要性。因此，在人工智能的能力与伦理考量之间达到最佳平衡，以确保其在医疗应用中公正中立地发挥作用至关重要。本叙述性综述聚焦于人工智能对医疗保健的影响以及以合乎伦理且平衡的方式加以应用以充分发挥其潜力的重要性。
