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Artificial Intelligence: Applications in Dentistry

Guest Editors:
Prabhat Kumar Chaudhari: All India Institute of Medical Sciences, India
Kunaal Dhingra: All India Institute of Medical Sciences, India
Raša Mladenović: University of Kragujevac, Serbia
Sergio Uribe: Riga Stradins University, Latvia/ Austral University of Chile, Chile


The Editors of BMC Oral Health have published this Collection on Artificial Intelligence: Applications in Dentistry. The applications of AI in dental sciences vary from dental emergencies to the differential diagnosis of orofacial pain, dental caries, and periodontal diseases, radiographic interpretations, and analysis of facial growth. However, despite the recognized need for artificial intelligence, implementing these systems has been minimal and slow. In this special Collection, we welcome papers related to the possible applications of AI in dental diagnosis and treatment.

Meet the Guest Editors

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Prabhat Kumar Chaudhari: All India Institute of Medical Sciences, India

Dr Prabhat Kumar Chaudhari, MDS, MFDS RCPS (Glasg), MFDS RCS (Eng), MDTFEd, MAMS, is an Associate Professor at the Division of Orthodontics and Dentofacial Deformities, Centre for Dental Education and Research, All India Institute of Medical Sciences, New Delhi, India. His main research interests focus on Artificial Intelligence applications in dentistry, 3D imaging, and 3D printing for dental and craniofacial medicine. Dr Chaudhari is a member of the prestigious International Telecommunication Union/WHO Focus Group on “Artificial Intelligence for Health” (FG-AI4H). 

Kunaal Dhingra: All India Institute of Medical Sciences, India

Dr Kunaal Dhingra, MDS, MFDS RCPS (Glasg), MFDS RCS (Eng), MDTFEd, MAMS, is an Associate Professor at the Division of Periodontics, Centre for Dental Education and Research, All India Institute of Medical Sciences, New Delhi, India. His research interests include clinical trials, systematic reviews, and microsurgery, including developing Artificial Intelligence-based periodontal clinical studies. Dr Dhingra is committed to exploring the applications of artificial intelligence and digital technology in Dentistry and training future generations of clinicians in these areas through education and research. He is a member of the prestigious International Telecommunication Union/WHO Focus Group on “Artificial Intelligence for Health” (FG-AI4H).

Raša Mladenović: University of Kragujevac, Serbia

Dr Raša Mladenović is an Assistant Professor at the University of Kragujevac, Serbia. Rasa specializes in Paediatric Dentistry and has dedicated a good part of his research to digital dentistry. Dr Mladenović works on projects developing technology-enhanced teaching methods in dental education. He is experienced in the programming of dedicated applications and educational promoting materials in the field of oral health and education. Dr Mladenović is also a member of the BMC Oral Health Editorial Board.

Sergio Uribe: Riga Stradins University, Latvia / Austral University of Chile, Chile

Dr Sergio Uribe (Ph.D., MSc, DDS) is an Associate Professor and Principal Investigator within the Department of Conservative Dentistry and Oral Health and the Bioinformatics Lab at Riga Stradins University and the Baltic Biomaterials Centre of Excellence (BBCE),  Latvia. Sergio is also an Associate Professor at the Austral University of Chile. In addition, he is contributing to the ITU/WHO Focus Group on Artificial Intelligence for Health (AI4H) as the Leading Research in the Cariology section of the “Dental diagnostics and digital dentistry” focus group.. Sergio completed his Ph.D. in Biomedical Sciences at the Austral University of Chile in 2016, after specialising as a maxillofacial radiologist in 2005 and receiving his DDS from the University of Valparaíso, Chile in 2000. 


About the collection

Artificial intelligence (AI) is the theory and development of computer systems that perform tasks typically requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. The human brain's visual cortex architecture inspires Deep Learning (DL). Hence DL produces artificial neural networks that can learn by themselves. These networks can deal with minor nuances and become faster and more precise the more data they analyse. Even in the primitive stage of its development, AI, for the last two to three decades, has drawn the attention of brilliant minds from both technical and clinical corners of the scientific community, thus making rapid strides. In most developing countries, the insufficiency of medical and dental specialists has increased the mortality of patients suffering from various diseases. In medical and dental applications, employing technology, especially artificial intelligence technology, could reduce cost, time, human expertise, and medical error. This approach can potentially revolutionise the dental public health scenario in developing countries. Clinical decision support systems and dental monitoring are computer programs that provide expert support for health professionals. The applications of AI in dental sciences vary from dental emergencies to the differential diagnosis of orofacial pain, dental caries, and periodontal diseases, radiographic interpretations, and analysis of facial growth. However, despite the recognized need for artificial intelligence, implementing these systems has been minimal and slow. In this special Collection, we welcome papers related to the possible applications of AI in dental diagnosis and treatment. BMC Oral Health has published this Collection to bring together research on:

  • AI and machine learning in dentistry
  • Application of AI in the diagnosis of dental diseases. 
  • Application of AI in the treatment planning of dental diseases. 
  • Developing new algorithms, technologies, and systems related to AI applications in dentistry.
  • Applications of AI in basic, clinical, and translational dental research.
  • Applications of AI in the diagnosis, treatment planning, treatment, and growth assessment of craniofacial deformities.
  • Ethical issues concerning AI research in dentistry.

We strongly recommended that authors refer to the minimum reporting guidelines for health research hosted by the EQUATOR Network when preparing their manuscript, and FAIRsharing.org for reporting checklists for biological and biomedical research, where applicable. Those appropriate for AI studies are listed below:

Artificial intelligence in dental research: Checklist for authors, reviewers, readers

For clinical trial reports for interventions involving AI, independent of the AI system modality (diagnostic, prognostic, therapeutic), we recommended following the CONSORT-AI Extension reporting guidelines. CONSORT-AI focuses on effectiveness and safety.

For clinical trial protocols for interventions involving AI we recommended following the SPIRIT-AI Extension reporting guidelines.

For reporting the early-stage clinical evaluation of decision support systems driven by AI we recommended following DECIDE-AI guidelines. These guidelines are used to report the early evaluation of artificial intelligence systems as an intervention in live clinical settings (small-scale, formative evaluation), independently of the study design and AI system modality (diagnostic, prognostic, therapeutic). Focuses on clinical utility, safety and human factors.

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist

Image Credits: IoT World Today

  1. Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous det...

    Authors: Yanshan Xiong, Hongyuan Zhang, Shiyong Zhou, Minhua Lu, Jiahui Huang, Qiangtai Huang, Bingsheng Huang and Jiangfeng Ding
    Citation: BMC Oral Health 2024 24:553
  2. The purpose of this study is to explore the perspectives, familiarity, and readiness of dental faculty members regarding the integration and application of artificial intelligence (AI) in dentistry, with a foc...

    Authors: Wajiha Qamar, Nadia Khaleeq, Anita Nisar, Sahibzadi Fatima Tariq and Mehreen Lajber
    Citation: BMC Oral Health 2024 24:542
  3. Oral cancer is a deadly disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop a fuzzy deep learning (FDL)-based model to estimate the survival time based on c...

    Authors: Rachasak Somyanonthanakul, Kritsasith Warin, Sitthi Chaowchuen, Suthin Jinaporntham, Wararit Panichkitkosolkul and Siriwan Suebnukarn
    Citation: BMC Oral Health 2024 24:519
  4. Ameloblastoma, a common benign tumor found in the jaw bone, necessitates accurate localization and segmentation for effective diagnosis and treatment. However, the traditional manual segmentation method is pla...

    Authors: Liang Xu, Kaixi Qiu, Kaiwang Li, Ge Ying, Xiaohong Huang and Xiaofeng Zhu
    Citation: BMC Oral Health 2024 24:55
  5. Adequate occlusal plane (OP) rotation through orthodontic therapy enables satisfying profile improvements for patients who are disturbed by their maxillomandibular imbalance but reluctant to surgery. The study...

    Authors: Jingyi Cai, Ziyang Min, Yudi Deng, Dian Jing and Zhihe Zhao
    Citation: BMC Oral Health 2024 24:30
  6. Accurate age estimation is vital for clinical and forensic purposes. With the rapid advancement of artificial intelligence(AI) technologies, traditional methods relying on tooth development, while reliable, ca...

    Authors: Se Hoon Kahm, Ji-Youn Kim, Seok Yoo, Soo-Mi Bae, Ji-Eun Kang and Sang Hwa Lee
    Citation: BMC Oral Health 2023 23:1007
  7. Owing to the remarkable advancements of artificial intelligence (AI) applications, AI-based detection of dental caries is continuously improving. We evaluated the efficacy of the detection of dental caries wit...

    Authors: Eun Young Park, Sungmoon Jeong, Sohee Kang, Jungrae Cho, Ju-Yeon Cho and Eun-Kyong Kim
    Citation: BMC Oral Health 2023 23:981
  8. Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed...

    Authors: Leran Tao, Meng Li, Xu Zhang, Mengjia Cheng, Yang Yang, Yijiao Fu, Rongbin Zhang, Dahong Qian and Hongbo Yu
    Citation: BMC Oral Health 2023 23:876
  9. Dental panoramic radiographs are utilized in computer-aided image analysis, which detects abnormal tissue masses by analyzing the produced image capacity to recognize patterns of intensity fluctuations. This i...

    Authors: Vyshiali Sivaram Kumar, Pradeep R. Kumar, Pradeep Kumar Yadalam, Raghavendra Vamsi Anegundi, Deepti Shrivastava, Ahmed Ata Alfurhud, Ibrahem T. Almaktoom, Sultan Abdulkareem Ali Alftaikhah, Ahmed Hamoud L Alsharari and Kumar Chandan Srivastava
    Citation: BMC Oral Health 2023 23:833
  10. The purpose of this study was to automatically classify the three-dimensional (3D) positional relationship between an impacted mandibular third molar (M3) and the inferior alveolar canal (MC) using a distance-...

    Authors: So-Young Chun, Yun-Hui Kang, Su Yang, Se-Ryong Kang, Sang-Jeong Lee, Jun-Min Kim, Jo-Eun Kim, Kyung-Hoe Huh, Sam-Sun Lee, Min-Suk Heo and Won-Jin Yi
    Citation: BMC Oral Health 2023 23:794
  11. The integration of artificial intelligence (AI) in dentistry has the potential to revolutionise the field of dental technologies. However, dental technicians’ views on the use of AI in dental technology are st...

    Authors: Galvin Sim Siang Lin, Yook Shiang Ng, Nik Rozainah Nik Abdul Ghani and Kah Hoay Chua
    Citation: BMC Oral Health 2023 23:690
  12. Having a reliable and feasible method to estimate whether an individual has reached 16 years of age would greatly benefit forensic analysis. The study of age using dental information has matured recently. In a...

    Authors: Shihui Shen, Zhuojun Zhou, Jian Wang, Linfeng Fan, Junli Han and Jiang Tao
    Citation: BMC Oral Health 2023 23:680
  13. Intra-oral scans and gypsum cast scans (OS) are widely used in orthodontics, prosthetics, implantology, and orthognathic surgery to plan patient-specific treatments, which require teeth segmentations with high...

    Authors: Shankeeth Vinayahalingam, Steven Kempers, Julian Schoep, Tzu-Ming Harry Hsu, David Anssari Moin, Bram van Ginneken, Tabea Flügge, Marcel Hanisch and Tong Xi
    Citation: BMC Oral Health 2023 23:643
  14. To evaluate the techniques used for the automatic digitization of cephalograms using artificial intelligence algorithms, highlighting the strengths and weaknesses of each one and reviewing the percentage of su...

    Authors: Huayu Ye, Zixuan Cheng, Nicha Ungvijanpunya, Wenjing Chen, Li Cao and Yongchao Gou
    Citation: BMC Oral Health 2023 23:467
  15. To assess and compare the impact of various computers aided design/manufacturing (CAD/CAM) materials on internal and marginal discrepancies, fracture resistance and failure probability of Endocrown restoration...

    Authors: Shaimaa Ahmed Abo El-Farag, Fatma Abdallah Elerian, Abdallah Ahmed Elsherbiny and Mahy Hassouna Abbas
    Citation: BMC Oral Health 2023 23:421
  16. Artificial intelligence (AI) has been introduced to interpret the panoramic radiographs (PRs). The aim of this study was to develop an AI framework to diagnose multiple dental diseases on PRs, and to initially...

    Authors: Junhua Zhu, Zhi Chen, Jing Zhao, Yueyuan Yu, Xiaojuan Li, Kangjian Shi, Fan Zhang, Feifei Yu, Keying Shi, Zhe Sun, Nengjie Lin and Yuanna Zheng
    Citation: BMC Oral Health 2023 23:358
  17. One of the main uses of artificial intelligence in the field of orthodontics is automated cephalometric analysis. Aim of the present study was to evaluate whether developmental stages of a dentition, fixed ort...

    Authors: Teodora Popova, Thomas Stocker, Yeganeh Khazaei, Yoana Malenova, Andrea Wichelhaus and Hisham Sabbagh
    Citation: BMC Oral Health 2023 23:274
  18. Preoperative planning of orthognathic surgery is indispensable for achieving ideal surgical outcome regarding the occlusion and jaws' position. However, orthognathic surgery planning is sophisticated and highl...

    Authors: Mengjia Cheng, Xu Zhang, Jun Wang, Yang Yang, Meng Li, Hanjiang Zhao, Jingyang Huang, Chenglong Zhang, Dahong Qian and Hongbo Yu
    Citation: BMC Oral Health 2023 23:161
  19. It is difficult for orthodontists to accurately predict the growth trend of the mandible in children with anterior crossbite. This study aims to develop a deep learning model to automatically predict the mandi...

    Authors: Jia-Nan Zhang, Hai-Ping Lu, Jia Hou, Qiong Wang, Feng-Yang Yu, Chong Zhong, Cheng-Yi Huang and Si Chen
    Citation: BMC Oral Health 2023 23:28

Submission Guidelines

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This Collection welcomes submission of Research Articles. Before submitting your manuscript, please ensure you have read our submission guidelines. Articles for this Collection should be submitted via our submission system, SNAPP. During the submission process you will be asked whether you are submitting to a Collection, please select "Artificial Intelligence: Applications in Dentistry" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process  and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.