Mechanical Properties of Collagen Implant Used in Neurosurgery Towards Industry 4.0/5.0 Reflected in ML Model

Collagen implants in neurosurgery are widely used due to their biocompatibility, biodegradability, and ability to support tissue regeneration, but their mechanical properties, such as low tensile strength and susceptibility to enzymatic degradation, remain challenging. Current technologies are improving these implants through cross-linking, synthetic reinforcements, and advanced manufacturing techniques such as 3D bioprinting to improve durability and predictability. Industry 4.0 is contributing to this by automating production, using data analytics and machine learning to optimize implant properties and ensure quality control. In Industry 5.0, the focus is shifting to personalization, enabling the creation of patient-specific implants through human–machine collaboration and advanced biofabrication. eHealth integrates digital monitoring systems, enabling real-time tracking of implant healing and performance to inform personalized care. Despite progress, challenges such as cost, material property variability, and scalability for mass production remain. The future lies in smart biomaterials, AI-driven design, and precision biofabrication, which could mean the possibility of creating more effective, accessible, and patient-specific collagen implants. The aim of this article is to examine the current state and determine the prospects for the development of mechanical properties of collagen implant used in neurosurgery towards Industry 4.0/5.0, including ML model.

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Publication Details

Journal
Applied Sciences
Published
2025-08-04
DOI
https://doi.org/10.3390/app15158630
Citations
2
Primary Topic
Bone Tissue Engineering Materials
Type
article
Field-Weighted Citation Impact
1.35

Funders

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Mechanical Properties of Collagen Implant Used in Neurosurgery Towards Industry 4.0/5.0 Reflected in ML Model

Izabela Rojek, Marek Andryszczyk, Dariusz Mikołajewski
2 citations
Applied Sciences
Bone Tissue Engineering Materials
1.35
article

Mechanical Properties of Collagen Implant Used in Neurosurgery Towards Industry 4.0/5.0 Reflected in ML Model

Izabela Rojek, Marek Andryszczyk, Dariusz Mikołajewski
article en
2 citations

Abstract

Collagen implants in neurosurgery are widely used due to their biocompatibility, biodegradability, and ability to support tissue regeneration, but their mechanical properties, such as low tensile strength and susceptibility to enzymatic degradation, remain challenging. Current technologies are improving these implants through cross-linking, synthetic reinforcements, and advanced manufacturing techniques such as 3D bioprinting to improve durability and predictability. Industry 4.0 is contributing to this by automating production, using data analytics and machine learning to optimize implant properties and ensure quality control. In Industry 5.0, the focus is shifting to personalization, enabling the creation of patient-specific implants through human–machine collaboration and advanced biofabrication. eHealth integrates digital monitoring systems, enabling real-time tracking of implant healing and performance to inform personalized care. Despite progress, challenges such as cost, material property variability, and scalability for mass production remain. The future lies in smart biomaterials, AI-driven design, and precision biofabrication, which could mean the possibility of creating more effective, accessible, and patient-specific collagen implants. The aim of this article is to examine the current state and determine the prospects for the development of mechanical properties of collagen implant used in neurosurgery towards Industry 4.0/5.0, including ML model.

Applied SciencesVol. 15(15)
Kazimierz Wielki University in Bydgoszcz (PL)
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Bone Tissue Engineering Materials
1.35
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Mechanical Properties of Collagen Implant Used in Neurosurgery Towards Industry 4.0/5.0 Reflected in ML Model — Izabela Rojek, Marek Andryszczyk, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS