scholarly journals Training atomic neural networks using fragment-based data generated in virtual reality

2020 ◽  
Vol 153 (15) ◽  
pp. 154105
Author(s):  
Silvia Amabilino ◽  
Lars A. Bratholm ◽  
Simon J. Bennie ◽  
Michael B. O’Connor ◽  
David R. Glowacki
2021 ◽  
pp. 49-52
Author(s):  
Gaurvi Vikram Kamra ◽  
Ankur Sharma

The concept of "articial intelligence" (AI) refers to machines that are capable of executing human-like tasks. AI can also be dened as a eld concerned with computational models that can reason and act intelligently. Perspicacious software for data computation has become a necessity as the amount of documented information and patient data has increased dramatically. The applicability, limitations, and potential future of AI-based dental diagnoses, treatment planning, and conduct are described in this concise narrative overview. AI has been used in a variety of ways, from processing of data and locating relevant information to using neural networks for diagnosis and the introduction of augmented reality and virtual reality in dental education. AI-based apps will improve patient care by relieving the dental workforce of tedious routine duties, improving population health at lower costs, and eventually facilitating individualized, anticipatory, prophylactic, and collaborative dentistry. The convergence of AI and digitization has ushered in a new age in dentistry, with tremendously promising future prospects.The applicability, limitations, and potential future of AI-based dental diagnoses, treatment planning, and conduct are described in this concise narrative overview.


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