Academic Journal

In Silico possibilities to understand peri-implant bone healing- state of the Art.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: In Silico possibilities to understand peri-implant bone healing- state of the Art.
Συγγραφείς: Nayak, Gargi Shankar, Al-Nawas, Bilal
Πηγή: International Journal of Implant Dentistry; 11/23/2025, Vol. 11 Issue 1, p1-11, 11p
Θεματικοί όροι: Dental implants, Artificial intelligence, Peri-implantitis, Finite element method, Computer simulation, Bone regeneration, Tissue mechanics
Περίληψη: Purpose: This scoping review was carried out to discover and compare all the possibilities the researchers have thought of in the recent past to perform in silico studies on bone healing after implantation of dental implants. Methods: An electronic search was conducted in Pubmed, Web of Science, Science Direct and google scholar database to find out related articles in dental peri-implant healing simulations from the period of 2010 until 2025. Results: In total, 40 articles were found relevant for this review. Different theories have been applied in the literature to simulate the mechanobiology of bone healing. Success has been found in predicting bone healing via in silico studies. The finite element was used often for these studies; however, the application of artificial intelligence is increasing with time in this sector. Conclusions: In silico platforms provide a non-invasive and fast approach to study the bone healing process. They can be used as an aid to predict peri-implant bone healing in dentistry. The rise of artificial intelligence in this sector opens a new path, where these studies can be performed with high accuracy at an astounding fast pace. These methods can be a boon to clinicians, patients as well as implant developers. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Implant Dentistry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Biomedical Index
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  – Url: https://dx.doi.org/doi:10.1186/s40729-025-00659-x
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  Data: In Silico possibilities to understand peri-implant bone healing- state of the Art.
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  Data: <searchLink fieldCode="AR" term="%22Nayak%2C+Gargi+Shankar%22">Nayak, Gargi Shankar</searchLink><br /><searchLink fieldCode="AR" term="%22Al-Nawas%2C+Bilal%22">Al-Nawas, Bilal</searchLink>
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  Data: International Journal of Implant Dentistry; 11/23/2025, Vol. 11 Issue 1, p1-11, 11p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Dental+implants%22">Dental implants</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Peri-implantitis%22">Peri-implantitis</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Bone+regeneration%22">Bone regeneration</searchLink><br /><searchLink fieldCode="DE" term="%22Tissue+mechanics%22">Tissue mechanics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: This scoping review was carried out to discover and compare all the possibilities the researchers have thought of in the recent past to perform in silico studies on bone healing after implantation of dental implants. Methods: An electronic search was conducted in Pubmed, Web of Science, Science Direct and google scholar database to find out related articles in dental peri-implant healing simulations from the period of 2010 until 2025. Results: In total, 40 articles were found relevant for this review. Different theories have been applied in the literature to simulate the mechanobiology of bone healing. Success has been found in predicting bone healing via in silico studies. The finite element was used often for these studies; however, the application of artificial intelligence is increasing with time in this sector. Conclusions: In silico platforms provide a non-invasive and fast approach to study the bone healing process. They can be used as an aid to predict peri-implant bone healing in dentistry. The rise of artificial intelligence in this sector opens a new path, where these studies can be performed with high accuracy at an astounding fast pace. These methods can be a boon to clinicians, patients as well as implant developers. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Implant Dentistry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1186/s40729-025-00659-x
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        Type: general
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      – SubjectFull: Peri-implantitis
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              Text: 11/23/2025
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