To address this issue, team led by the University of Michigan School of Dentistry developed a machine learning algorithm,
– a form of artificial intelligence to find out competent patient for regenerative outcomes after surgical treatments of peri-implantitis.
“Regenerative therapy for peri-implantitis is expensive and treatment outcomes are unpredictable,” said first author Jeff Wang, U-M clinical assistant professor and principal investigator for the regenerative treatment of peri-implantitis clinical trial.
In designing the algorithm more emphasis is given to identify the immune cell types capable of wound healing and tissue repair for microbial control correlate with superior clinical outcome.
Though FARDEEP decides the personalized old implant replacement option for regenerative therapy for peri-implantitis, more human clinical trials are required to be used by clinicians.
Source: Eurekalert
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