{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T00:57:55Z","timestamp":1793235475610,"version":"4.5.0"},"reference-count":50,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T00:00:00Z","timestamp":1758153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan","award":["BR24992786"],"award-info":[{"award-number":["BR24992786"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JFB"],"abstract":"<jats:p>The reconstruction of segmental bone defects requires patient-specific scaffolds that combine mechanical safety, biological functionality, and rapid manufacturing. We converted CT-derived mandibular geometry into a functionally graded Ti-6Al-4V lattice and optimised porosity, screw layout, and strut thickness through a cyber-physical loop that joins high-fidelity FEM, millisecond ANN, and a BN for uncertainty quantification. Fifteen candidate scaffolds were fabricated by direct metal laser sintering and hot isostatic pressing and were mechanically tested. FEM predicted stress and stiffness with 98% accuracy; the ANN reproduced these outputs with 94% fidelity while evaluating 10,000 designs in real time, and the BN limited failure probability to &lt;3% under worst-case loads. The selected 55\u201365% porosity design reduced titanium use by 15%, shortened development time by 25% and raised multi-objective optimisation efficiency by 20% relative to a solid-plate baseline, while resisting a 600 N bite with a peak von Mises stress of 225 MPa and micromotion &lt; 150 \u00b5m. Integrating physics-based simulation, AI speed, and probabilistic rigour yields a validated, additively manufactured scaffold that meets surgical timelines and biomechanical requirements, offering a transferable blueprint for functional scaffolds in bone and joint surgery.<\/jats:p>","DOI":"10.3390\/jfb16090350","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T09:32:32Z","timestamp":1758187952000},"page":"350","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Data-Driven Design and Additive Manufacturing of Patient-Specific Lattice Titanium Scaffolds for Mandibular Bone Reconstruction"],"prefix":"10.3390","volume":"16","author":[{"given":"Nail","family":"Beisekenov","sequence":"first","affiliation":[{"name":"Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX 77843, USA"},{"name":"Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bagdat","family":"Azamatov","sequence":"additional","affiliation":[{"name":"Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, 19 Serikbayev Street, Ust-Kamenogorsk 070010, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2870-6668","authenticated-orcid":false,"given":"Marzhan","family":"Sadenova","sequence":"additional","affiliation":[{"name":"Center of Excellence \u201cVERITAS\u201d, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk 070004, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5589-1638","authenticated-orcid":false,"given":"Dmitriy","family":"Dogadkin","sequence":"additional","affiliation":[{"name":"Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, 19 Serikbayev Street, Ust-Kamenogorsk 070010, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniyar","family":"Kaliyev","sequence":"additional","affiliation":[{"name":"Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, 19 Serikbayev Street, Ust-Kamenogorsk 070010, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2740-9143","authenticated-orcid":false,"given":"Sergey","family":"Rudenko","sequence":"additional","affiliation":[{"name":"Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, 19 Serikbayev Street, Ust-Kamenogorsk 070010, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boris","family":"Syrnev","sequence":"additional","affiliation":[{"name":"Center of Excellence \u201cVERITAS\u201d, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk 070004, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1007\/s11517-019-02104-9","article-title":"Finite Element Analysis of Bone and Implant Stresses for Customized 3D-Printed Orthopaedic Implants in Fracture Fixation","volume":"58","author":"Yan","year":"2020","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Han, C., Yan, F., Yuan, D., Li, K., Yang, Y., Zhang, J., and Wang, D. (2024). Machine Learning Enabling Prediction in Mechanical Performance of Ti6Al4V Fabricated by Large-Scale Laser Powder Bed Fusion via a Stacking Model. Front. Mech. 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