Balgude Shalini Dhananjay, Gite Shilpa, Pradhan Biswajeet, Lee Chang-Wook
Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis Institute of Technology, Symbiosis International (Deemed University) (SIU), Pune, Maharasthra, India.
AI & ML Department, Symbiosis Institute of Technology (Pune Campus), Symbiosis International Deemed University, Pune, Maharasthra, India.
PeerJ Comput Sci. 2024 Nov 27;10:e2505. doi: 10.7717/peerj-cs.2505. eCollection 2024.
Cerebral palsy (CP) is a group of disorders that alters patients' muscle coordination, posture, and movement, resulting in a wide range of deformities. Cerebral palsy can be caused by various factors, both prenatal and postnatal, such as infections or injuries that damage different parts of the brain. As brain plasticity is more prevalent during childhood, early detection can help take the necessary course of management and treatments that would significantly benefit patients by improving their quality of life. Currently, cerebral palsy patients receive regular physiotherapies, occupational therapies, speech therapies, and medications to deal with secondary abnormalities arising due to CP. Advancements in artificial intelligence (AI) and machine learning (ML) over the years have demonstrated the potential to improve the diagnosis, prognosis, and management of CP. This review article synthesizes existing research on AI and ML techniques applied to CP. It provides a comprehensive overview of the role of AI-ML in cerebral palsy, focusing on its applications, benefits, challenges, and future prospects. Through an extensive examination of existing literature, we explore various AI-ML approaches, including but not limited to assessment, diagnosis, treatment planning, and outcome prediction for cerebral palsy. Additionally, we address the ethical considerations, technical limitations, and barriers to the widespread adoption of AI-ML for CP patient care. By synthesizing current knowledge and identifying gaps in research, this review aims to guide future endeavors in harnessing AI-ML for optimizing outcomes and transforming care delivery in cerebral palsy rehabilitation.
脑瘫是一组会改变患者肌肉协调性、姿势和运动的疾病，会导致多种畸形。脑瘫可由产前和产后的各种因素引起，如感染或损伤，这些因素会损害大脑的不同部位。由于儿童时期大脑可塑性更为普遍，早期检测有助于采取必要的管理和治疗措施，通过改善患者生活质量使其显著受益。目前，脑瘫患者接受定期的物理治疗、职业治疗、言语治疗和药物治疗，以应对因脑瘫引起的继发性异常。多年来，人工智能（AI）和机器学习（ML）的进展已显示出改善脑瘫诊断、预后和管理的潜力。这篇综述文章综合了应用于脑瘫的人工智能和机器学习技术的现有研究。它全面概述了人工智能-机器学习在脑瘫中的作用，重点关注其应用、益处、挑战和未来前景。通过对现有文献的广泛研究，我们探索了各种人工智能-机器学习方法，包括但不限于脑瘫的评估、诊断、治疗规划和结果预测。此外，我们还讨论了在脑瘫患者护理中广泛采用人工智能-机器学习的伦理考量、技术限制和障碍。通过综合当前知识并找出研究差距，本综述旨在指导未来利用人工智能-机器学习优化脑瘫康复结果和转变护理方式的努力。
