AI has made its mark in every sector, making it more powerful. In this article, we are discussing the chances and challenges of AI in dentistry.
Chances Of AI In Dentistry
AI is being used in dentistry in various applications. Following are chances of AI in dentistry:
AI in Oral Cancer Detection
Neural networks are used to assess images of oral cancer lesions to facilitate early detection as well as diagnosis. Moreover, the chances of oral cancer survival depend on early diagnosis. Therefore, it is imperative that clinicians perform screening at recall visits. And to assist this process, more applications are being developed and leveraged for image capture of lesions. Additionally, advancements within the application are being incorporated in deep learning to distinguish between pictures irrespective of signs of oral cancer.
AI Can Be Used To Detect Dental Disease
AI can enhance the quality of image detection, classification, and categorization in the dental field. For instance, CNN’s can determine dental decay depending on identifying the location and morphology of the various lesions through radiography. There are presently various AI investigational devices that are approved to be used in dentistry. The dental software can create a set of nodes as well as connections that collect and apply to learn through seeing the data is available. The software leverages cloud-based algorithms as well as automatically pinpoint areas of the decay determined on the digital radiographs. Primarily, it can predict caries using CNN image detection and can easily be incorporated into current workflows.
AI In Dental Office Management
AI can be used for communication with patients as well as marketing. From booking appointments, assessing data to fulfilling marketing agenda AI can be used in various segments. Additionally, the neural network can mine data and determine decreased productivity periods. The algorithm can also monitor appointments, cancellations, meetings, etc.
Challenges Of AI In Dentistry
While the potential of AI is immense, AI solutions are getting to be adopted in standard medical practices. In terms of dentistry, the convolution neural networks have only been integrated with the research settings. The adoption came in 2015, and it is used mainly on dental radiographs, and the application has moved towards the clinical areas. Even when there are many potentials for its application, the dentistry sector has yet to adopt AI effectively. And there may be may three reasons for the same:
- Data in the medical and dental field lacks accessibility and availability because of data protection concerns. The data is often secured within the individualized and segregated interoperable system. Additionally, these datasets lack structure and generally are small when compared to other datasets in the AI landscape. Data for every patient is multi-dimensional, complex, and sensitive, with limited options for validating them.
- Processing data and measuring and authenticating the result may be inadequately replicable and powerful in AI research in the dental landscape. It is not clear how datasets were selected and preprocessed. Oftentimes, data is used for training as well as testing, resulting in data snooping bias. It is generally not possible to define the gold standard and lacks agreement on how experts are required to label the data point and merge on different labels.
- Results of AI in dentistry are generally not readily applicable. A piece of information offered by dental AI applications will only partially educate the required and complicated decision-making in dental care. Additionally, transparency and responsibilities remain questions.
The Bottom Line
AI is a technology that has been transformative in various sectors, including dentistry. The potential of this technology is yet at its inception in the dental realm. The sector continues to explore the challenges and chances that this technology holds.