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Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

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Osseointegration Pharmacology: A Systematic Mapping Using Artificial Intelligence.

Mohammed Mahri¹, Nicole Shen², Francisco Berrizbeitia³

¹Faculty of Dentistry, McGill University, Montreal, QC, Canada; Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Jazan University, Jazan, Saudi Arabia.

Acta Biomaterialia

|November 12, 2020

Summary

This summary is machine-generated.

A new machine learning algorithm automates literature reviews on how medications affect osseointegration (bone fusion with implants). This tool significantly reduces workload and improves the assessment of drug impacts on medical device performance.

Keywords:

artificial intelligence automated screening bone-implant contact dental implants drugs machine learning osseointegration pharmacological agents prosthetic implants systematic mapping

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Area of Science:

Biomaterials Science
Pharmacology
Computational Biology

Background:

Medications can negatively impact osseointegrated implant performance.
Systematic reviews are effective for single drugs but impractical for comprehensive medication analysis.
Evidence mapping is resource-intensive when performed manually.

Purpose of the Study:

To develop a machine learning algorithm for automated literature mapping of medication effects on osseointegration.
To assess the feasibility of using machine learning for large-scale evidence mapping in this field.

Main Methods:

Trained a Support Vector Machines (SVM) based machine learning algorithm using manually classified datasets.
Validated the algorithm and applied it to screen nearly 600,000 articles.
Utilized an extremely sensitive search strategy to identify relevant literature.

Main Results:

The algorithm screened 599,604 articles, identifying 281 relevant studies on 31 drugs.
Achieved 95% accuracy in literature screening.
Reduced manual screening workload by 93% compared to traditional methods.

Conclusions:

Machine learning-driven evidence mapping is a highly accurate and efficient method for assessing medication effects on osseointegration.
Drugs influencing homeostasis, inflammation, cell proliferation, and bone remodeling significantly affect osseointegrated device outcomes.
This approach enables comprehensive assessment of all medications' impact on osseointegrated medical devices.