Chandra Hasa J M, Narayanan P, Pramanik R, Arockiarajan A
Department of Aerospace Engineering, Indian Institute of Technology Madras, 600036 Chennai, India.
Department of Mechanical Engineering, Indian Institute of Technology Madras, 600036 Chennai, India.
Biomed Mater. 2025 Jan 22;20(2). doi: 10.1088/1748-605X/ada840.
Machine learning (ML) has emerged as a transformative tool in various industries, driving advancements in key tasks like classification, regression, and clustering. In the field of chemical engineering, particularly in the creation of biomedical devices, personalization is essential for ensuring successful patient recovery and rehabilitation. Polylactic acid (PLA) is a material with promising potential for applications like tissue engineering, orthopedic implants, drug delivery systems, and cardiovascular stents due to its biocompatibility and biodegradability. Additive manufacturing (AM) allows for adjusting print parameters to optimize the properties of PLA components for different applications. Although past research has explored the integration of ML and AM, there remains a gap in comprehensive analyses focusing on the impact of ML on PLA-based biomedical devices. This review examines the most recent developments in ML applications within AM, highlighting its ability to revolutionize the utilization of PLA in biomedical engineering by enhancing material properties and optimizing manufacturing processes. Moreover, this review is in line with the journal's emphasis on bio-based polymers, polymer functionalization, and their biomedical uses, enriching the understanding of polymer chemistry and materials science.
机器学习（ML）已成为各行业中具有变革性的工具，推动了分类、回归和聚类等关键任务的进展。在化学工程领域，特别是在生物医学设备的制造中，个性化对于确保患者成功康复至关重要。聚乳酸（PLA）因其生物相容性和可生物降解性，在组织工程、骨科植入物、药物输送系统和心血管支架等应用中具有广阔的潜力。增材制造（AM）允许调整打印参数，以优化PLA组件在不同应用中的性能。尽管过去的研究已经探索了ML与AM的整合，但在聚焦ML对基于PLA的生物医学设备影响的全面分析方面仍存在差距。本综述考察了AM中ML应用的最新进展，强调了其通过增强材料性能和优化制造工艺，彻底改变PLA在生物医学工程中应用的能力。此外，本综述符合该期刊对生物基聚合物、聚合物功能化及其生物医学用途的关注重点，丰富了对聚合物化学和材料科学的理解。
