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All Journal CESS (Journal of Computer Engineering, System and Science) Al-Adyan: Jurnal Studi Lintas Agama al-Afkar, Journal For Islamic Studies Aptisi Transactions on Management CCIT (Creative Communication and Innovative Technology) Journal ADI Journal on Recent Innovation (AJRI) JOURNAL EDUCATIONAL OF NURSING(JEN) Jurnal Investasi ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Tahdzibi: Manajemen Pendidikan Islam Journal of Information System and Technology (JOINT) SATIN - Sains dan Teknologi Informasi Seminar Nasional Inovasi Teknologi
Abdul Hamid Arribathi
Universitas Raharja
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Nursing Social Sciences Other

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Integrating Artificial Intelligence with 3D Printing Technology in Healthcare: Sustainable Solutions for Clinical Training Optimization Ikhsan, Ramzi Zainum; Rahayu, Sri; Arribathi, Abdul Hamid; Azizah, Nur
ADI Journal on Recent Innovation Vol. 6 No. 2 (2025): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v6i2.1126

Abstract

Integrating Artificial Intelligence (AI) with 3D printing technology offers transformative solutions in healthcare, specifically improving clinical training through precise and customizable replicas of human anatomy. Traditional training methods face challenges such as limited access to high quality models, lack of precision, adaptability, and the environmental impact of resource use. This study employed a mixed methods approach, combining quantitative analysis of model accuracy and input from healthcare professionals, to evaluate the effectiveness of AI optimized 3D printing. The focus was on AI enhanced 3D printing models designed for healthcare training. Traditional methods often lack precision, adaptability, and scalability, limiting their effectiveness in dynamic healthcare scenarios. AI based 3D printing reduces material use by 30\% while providing high quality, customized training models, improving accessibility and sustainability. This research highlights the potential of AI and 3D printing integration to drive technological innovation, align healthcare training with Sustainable Development Goals (SDGs), and promote a more sustainable and efficient future in medical education.
Co-Authors Abdillah, Muhammad Ardiansyah Abdul Hayat Abdul Munir Ahmad Roihan Anggraeni, Lisda Dedeh Supriyanti Dwiharyanto, Muhammad Adrian Erlangga, Mahesa Fransiska Dika Mega Rosita Gestiarie, Riska Putri Gilang Kartika Hanum Haris Haris Ikhsan, Ramzi Zainum Ilamsyah Ilamsyah, Ilamsyah jawahir, Jawahir Jungjunan, Sunan Reihan leon yudi haryanto leon Lisda Anggraeni Lusyani Sunarya Maimunah, Maimunah Marfuddin, Ade Margono Mitrohardjono Mitrohardjono, Margono Nuke Puji Lestari Santoso Nur Azizah Nurdin Suryana Nurfitriani, Devi Nurussaadah Nurussaadah Putra, Ardy Dzaky Abiyyu Putra, Lingga Buana Qurotul Aini Rinaldy Qodar Saputra Riska Putri Gestiarie Saryani Saryani Saryani SRI RAHAYU Syah, Adith Adriyan Tandilintin, Abert Untung Rahardja Wahyu Hidayat