The system for diagnosis of periodontitis based on dental X-ray images, a product developed by VNU Information Technology Institute helps doctors to make more accurate decisions about possible diseases and have treatment directions for reference.

Currently, great advances in the field of imaging - an application of science and technology to explore the structures of the human body, represented by conventional images, have made early diagnosis and identification of many diseases in order to provide the most effective treatment or surgical method. The demand for orthodontics as well as dental care is increasing in modern life. For patients when coming to dental care and treatment, being treated correctly, fully and wholeheartedly is the top factor. For accurate treatment, dental diagnosis is the most important aspect in modern dentistry. An accurate diagnosis helps to quickly make a medical record and plan a successful treatment. Therefore, computer-based medical diagnostic systems are of great interest to doctors because they help to make more accurate decisions about possible diseases and have treatment directions for reference.

The necessity of applying artificial intelligence in supporting the diagnosis of medical diseases is an indispensable need, helping to reduce the examination process and increase the ability to detect diseases on patients. In this demo, we present a website-based homogenous system incorporating the latest Deep Learning methods to assist doctors in diagnosing Perenitis on apical X-ray images. After a process of research, the team gave a test result on X-ray film that was very good when compared with the doctor's diagnosis in diagnosing Perianitis and a complete system was used by the School of Odonto-Stomatology - Hanoi Medical University.

Based on the professional requirements of the doctor, the team analyzed and designed the software with the following main functions to meet the set requirements.

The functions for doctors and clinicians:

1. X-ray imaging of peri-pedunculitis using deep learning technology. The doctor will select the image from the personal computer, enter the patient information and select the diagnosis, the software will return the results displayed on the screen.

2. Track your medical history. The doctor can choose the examination history by week, month, ... the software will return the examination history results displayed on the screen.

3. Follow up patient list. Doctors can sort, search for patients by name, date of examination, the software will return the results of the examination history displayed on the screen.

4. Personal account management. The doctor can change the personal information, password, profile picture of the account.

5. Home system statistics. The system will display the doctor's statistics about the number of patients, the number of photos, the photo graph, the chart of visits, ... The software will return the results of the examination history displayed on the screen.

The functions for Information Technology specialist:

1. System statistics home page. The system will display the Specialist's statistics on the number of patients, the number of photos, photo histograms, histograms of visits, ... The software will return the results of the examination history displayed on the screen.

2. Manage your Doctor's account. Experts can add, edit, delete doctors.

3. Train the deep learning model. Experts can select parameters, models, and train deep learning models. The software will run the training process in the background.

4. Set up a deep learning model. The expert will choose a deep learning model for the doctor's diagnosis. The software will configure the deep learning model.

Some advantages of the software:

- Deep learning model is trained to diagnose accurately and efficiently.

- The storage system ensures the integrity of data of doctors and patients.

- User-friendly display interface for Doctors and IT Professionals.

- Deployed on the Internet, allowing access anytime, anywhere.

- Detailed and complete tracking and statistics of important information.

After a period of research and development, the team released a complete version and handed over the product to the Doctor. Since then, we have received positive feedbacks from the doctors, in addition to correction suggestions to increase the perfection of the software. With this product, the team hopes that this will be a premise for information technology products applied in medical diagnosis, especially dental imaging.