TY - JOUR
T1 - A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques
AU - Memon, Afaque Rafique
AU - Li, Jianning
AU - Egger, Jan
AU - Chen, Xiaojun
N1 - Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - Introduction: Researchers and engineers have found their importance in healthcare industry including recent updates in patient-specific implant (PSI) design. CAD/CAM technology plays an important role in the design and development of Artificial Intelligence (AI) based implants. The across the globe have their interest focused on the design and manufacturing of AI-based implants in everyday professional use can decrease the cost, improve patient’s health and increase efficiency, and thus many implant designers and manufacturers practice. Areas covered: The focus of this study has been to manufacture smart devices that can make contact with the world as normal people do, understand their language, and learn to improve from real-life examples. Machine learning can be guided using a heavy amount of data sets and algorithms that can improve its ability to learn to perform the task. In this review, artificial intelligence (AI), deep learning, and machine-learning techniques are studied in the design of biomedical implants. Expert opinion: The main purpose of this article was to highlight important AI techniques to design PSIs. These are the automatic techniques to help designers to design patient-specific implants using AI algorithms such as deep learning, machine learning, and some other automatic methods.
AB - Introduction: Researchers and engineers have found their importance in healthcare industry including recent updates in patient-specific implant (PSI) design. CAD/CAM technology plays an important role in the design and development of Artificial Intelligence (AI) based implants. The across the globe have their interest focused on the design and manufacturing of AI-based implants in everyday professional use can decrease the cost, improve patient’s health and increase efficiency, and thus many implant designers and manufacturers practice. Areas covered: The focus of this study has been to manufacture smart devices that can make contact with the world as normal people do, understand their language, and learn to improve from real-life examples. Machine learning can be guided using a heavy amount of data sets and algorithms that can improve its ability to learn to perform the task. In this review, artificial intelligence (AI), deep learning, and machine-learning techniques are studied in the design of biomedical implants. Expert opinion: The main purpose of this article was to highlight important AI techniques to design PSIs. These are the automatic techniques to help designers to design patient-specific implants using AI algorithms such as deep learning, machine learning, and some other automatic methods.
KW - Artificial Intelligence (AI)
KW - automatic implant design
KW - deep learning
KW - implant design
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85115725824&partnerID=8YFLogxK
U2 - 10.1080/17434440.2021.1969914
DO - 10.1080/17434440.2021.1969914
M3 - Review article
C2 - 34404280
AN - SCOPUS:85115725824
SN - 1743-4440
VL - 18
SP - 985
EP - 994
JO - Expert Review of Medical Devices
JF - Expert Review of Medical Devices
IS - 10
ER -