Introduction

What is artificial intelligence? 

AI is an abbreviation of the phrase (Artificial intelligence) which describes a field of computer science that imitates the human brain in critical thinking, problem-solving and decision-making. It was introduced in 1956 by John McCarthy, at that time it was called (Machine intelligence) and developed after the Fourth Industrial Revolution to be known as Artificial intelligence.¹ AI in recent days has attracted the attention of scientists all over the globe, it’s a technology that has evolved rapidly, as the idea of combining the reliability of a machine and human intelligence and consciousness with one tool was a desire of many researchers and investigators. 

Artificial intelligence technology has a neural network with interconnected artificial neurons - like the neurons of the human nervous system - that are designed for the human to compute signals. It mimics human thoughts and works as data storage, analyzing and processing systems to solve a particular problem.¹

What are the benefits of AI in healthcare compared to traditional methods?

• Accuracy and faster performance of the repetitive tasks make it more efficient
• Gathering a larger amount of data and analysing it helps in decision-making and problem-solving 
• It minimises the errors, hazards and mistakes that humans could make 
• It saves time and decreases the needed manpower 
• It provides a personal treatment plan and recommendation for each patient (customization)
• It allows real-time accessibility of data and services.¹

Artificial intelligence and its application in healthcare systems 

Overview 

The use of AI in health, especially in dentistry, has exploded in recent years. Traditional treatment methods have transformed into digital methods by the launching of new AI software programs that use virtual and robotic AI tools.¹ AI is being implemented in various departments of healthcare to make tasks more accurate and faster. Functions such as processing of patient data, classifying, arranging, making appointments, diagnosing, imaging, treatment planning, rehabilitation and robotic-supported surgeries in all medical fields including dentistry have been made more user-friendly and time-efficient.¹

How can AI help in diagnosis, prognosis and treatment planning? 

AI in its simplest form, consists of inputs and outputs, these inputs can be images, audio or texts that are supplied to the AI system. These inputs pass through the machine which processes them and generates results that could describe the patient's diagnosis, treatment plan, prognosis and outcome regarding the provided information (inputs).¹

AI application in dentistry

AI in dental education 

AI tools are being implemented in educational processes in universities and other educational centres for students at the pre-clinical level by creating scenarios that mimic clinical work on real patients. Students can train using AI tools before performing procedures on real patients. This significantly minimises clinical errors and hazards that may affect the patients. 

These scenarios also allow students to assess their work and discover their weaknesses, start fixing them before reaching the clinical level which results in more successful treatment for the patients. 

Numerous studies found that students educated with an AI system developed clinical skills quicker than those who trained with the conventional system.¹ 

AI in patient management 

Artificial intelligence-powered virtual dental assistants may help in doing multiple tasks like:

• scheduling appointments
• taking a patient's history (name, age, gender, habits like smoking or drinking in addition to patient both medical and dental history) 
• making information available to the dentist before the appointment starts which helps in reducing the consumed time 
• Arranging a patient's papers and medical insurance can be done with the aid of an AI virtual assistant 

All of the above-mentioned tasks could be done more efficiently and accurately minimizing human mistakes and decreasing the manpower needed.¹ 

AI in diagnosis

Data analysis

AI can analyze and manage a large amount of data that helps the dentist to make the right decision regarding the diagnosis and personalised treatment plan for each patient.  

Disease detection

AI assists in detecting and tracking the symptoms and vital signs of the patient and other data that could help to identify potential health issues. AI, with the aid of this patient’s stored data, discovers the likelihood of developing a certain medical disease, condition or complication and can assist in preventing it.¹

Imaging 

Using AI tools in imaging has significant advantages, it assists the radiologist just focusing and concentrating on the interpretation of very complex pathologies while keeping the regular interpretation for the machines which contributes to saving considerable time.¹

Conventional CBCT scans with low sensitivity to tooth fractures have been developed into the high resolution-CBCT scan which can detect, quantify and localize the fracture line and cracks in the tooth using machine learning methods.

The same CBCT scan with the aid of the CNN model (which is a network architecture for deep learning that learns directly from data which is useful for finding patterns in images to recognise objects, classes, and categories) is found to be very useful in detecting mucosal thickening and mucous retention in case of maxillary sinus diseases.  

Deep learning methods (DL detecting methods) were found to have an effective and superior role in discovering salivary gland diseases and the percentage for recurrence of malignancies and this is just for inclusion and not limitation.² All these satisfying results of correct and accurate diagnosis result from training and providing the database with many images and scans to make the machine able to recognize the abnormalities.

Periodontal disease detection

A further example of AI's role in the diagnosis of dental diseases is the tools that have been involved in the diagnosis of periodontal diseases which represent a global problem that affects billions of people all around the world. Early diagnosis of periodontal diseases which affect both the function and aesthetics of the patient, was found to improve the patient's dental status and the overall quality of life.¹ 

TMJ disorders

Another concept called the artificial neural network (ANN system) which is an integrated part of machine learning was tested by identifying a sample of normal patients and others with unilateral or bilateral non-reducing disks. It was found that AI simplifies and helps in diagnosing the problem with an acceptable error percentage and is affordable and cost-effective Other experiments and studies have also proven the effectiveness of AI tools in the detection of Temporomandibular joint (TMJ) disorders.¹

AI in the formulation of the treatment plan 

After the AI system gathers the necessary patient data including the history and examination results, it recommends a treatment plan that is personalized for each patient, then it will use them for prediction of the treatment outcome and prognosis.² 

What are the challenges that AI applications could face in healthcare systems? 

A diverse set of challenges may face the adoption of advanced AI technologies in healthcare fields. These include:³

• Data access
• Data quality
• Availability of the infrastructure
• Staff training
• Qualified staff to deal with the advanced machines and software
• Affordability of the machines. 
• Patient data confidentiality and security 

Summary

AI has transformed the field of dentistry and enhanced efficiency, accuracy and customization of the patient's diagnosis, treatment plan, prediction of prognosis and outcomes. 

It also plays a significant role in students’ educational and training processes, using scenarios that mimic the human body. Additionally, AI has proven its effectiveness in image interpretation in case of bone and teeth fractures, TMJ problems, periodontal conditions, maxillary sinus and salivary gland diseases. Furthermore, it plays an important role in patient management as an integral part of the diagnostic process. It saves time, decreases the need for human and manpower efforts and speeds up the whole management process. 

Despite all these benefits, numerous challenges are facing the implementation of AI in the healthcare field including data access and security, availability of infrastructures and trained personnel and affordability and cost-effectiveness.