ABSTRACT
@#At present, implant surgery robots have basically achieved "surgical intelligence", but "brain-inspired intelligence" of robots is still in the stage of theory and exploration. The formulation of a clinical implantation plan depends on the timing of implantation, implantation area, bone condition, surgical procedure, patient factors, etc., which need to evaluate the corresponding clinical decision indicators and clinical pathways. Inspired by evidence-based medicine and the potential of big data and deep learning, combined with the data characteristics of clinical decision indicators and clinical pathways that can be quantitatively or qualitatively analyzed, this review simulates the cognitive behavior and neural mechanisms of the human brain and proposes a feasible brain-inspired intelligence scheme by predicting the decision indices and executing clinical pathways intelligently, that is, "select clinical indicators and clarify clinical pathways -- construct database -- use deep learning to intelligently predict decision indicators -- intelligent execution of clinical pathways -- brain-inspired intelligence of implant decision-making". Combined with the previous research results of our team, this review also describes the process of realization of brain-inspired intelligence for immediate implant timing decisions, providing an example of the comprehensive realization of brain-inspired intelligence of implant surgery robots in the future. In the future, how to excavate and summarize other clinical decision factors and select the best way to realize the automatic prediction of evidence-based clinical indicators and pathways and finally realize the complete intellectualization of clinical diagnosis and treatment processes will be one of the directions that dental clinicians need to strive for.
ABSTRACT
@#With the arrival of the era of big data, increasing attention has been drawn to the application of artificial intelligence (AI) in the medical field. AI has many advantages, such as objectivity, accuracy, minimal invasiveness, time savings and high efficiency. Therefore, the combination of AI with dental diagnosis and treatment can help dentists improve work efficiency and save medical resources, offering potential significant benefits for dental application. At present, AI has been gradually integrated into prosthodontics, oral and maxillofacial surgery, orthodontics, endodontics and periodontics. The AI system can realize automatic tooth preparation, automatic tooth arrangement and implantology. Deep learning can be used to assist in diagnosing maxillary sinus inflammation, predicting the complications of tooth extraction and improving the accuracy of osteotomy. The AI system can also provide significant clues for the diagnosis, treatment and prognosis of oral and maxillofacial tumors. The breakthrough brought by AI in cephalometric and the assessment of facial attractiveness of patients has promoted the development of intelligent and personalized orthodontic treatment. Deep learning and analysis of medical images also promote the accuracy of root canal therapy as well as the diagnosis and treatment of periodontal diseases. AI technology has realized the leap from digitalization to automation and intelligence in oral diagnosis and treatment, and its application potential in the oral field should not be underestimated. Based on the concepts of AI, this paper will focus on the application of artificial intelligence in various oral clinical fields and briefly introduce its advantages, problems and future.
ABSTRACT
The intelligent level of the modern medical equipments is higher than before and the automatic calibration circuits are largely used. The control circuit of the intelligent equipments is quite complicated and its working modes have been simplified to four-terminal or double terminal nets. The intelligent medical equipments such as CT, MRI, DR, PET/ CT have more chances to have some "soft" errors that are usually related to the zero-line calibration. In actual use, it can be noticed and performed, and the detecting and servicing for the medical equipments can be much easier than before.