The Impact of Clinical Artificial Intelligence in the Digital Workflow in Dentistry - A Narrative Review

Abstract

Abstract Artificial intelligence (AI) is progressively emerging as a significant instrument for enhancing clinical processes due to the quick development of digital technology in dentistry. Digital radiographs, CBCT scans, intraoral scans, and electronic health records all produce vast volumes of complicated data that might be challenging to manually analyze in modern dentistry practices. By evaluating these datasets, AI systems may assist physicians in identifying anomalies, assisting with treatment planning, and directing decision-making. By automating processes like picture segmentation, margin detection, and prosthetic design, such systems could improve diagnosis accuracy, decrease clinician variability, and streamline operations. Despite its potential, AI incorporation into routine dentistry treatment is still in its infancy due to issues with dataset quality, algorithm transparency, ethical considerations, and clinician acceptability. Research indicates promising improvements in workflow and diagnosis accuracy, but there is still little data on actual results. Clinical decision-making may benefit greatly from AI, but its efficacy requires meticulous validation and cautious integration with current digital procedures. It is therefore essential to comprehend the possibilities and constraints of AI in dentistry. An overview of recent studies on clinical AI applications in digital workflows is given in this review, which emphasizes how AI may help with diagnosis and treatment planning while also pointing out areas that require more research to guarantee safe and efficient use in everyday practice.

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