Qi, J., Chen, J., Pang, Y., Guo, Y., Chen, G., Liu, Y., Wang, J. (2023) ‘Association between periodontal disease and osteoporosis in postmenopausal women: a systematic review and meta-analysis’, Heliyon, 9(11). Introduction Although women represent a significant proportion of the patient population, female representation in the fields of dental and medical research has been consistently[…]

Umer, F., Adnan, S. & Lal, A. Research and application of artificial intelligence in dentistry from lower-middle income countries – a scoping review. BMC Oral Health 24, 220 (2024). Introduction Artificial Intelligence (AI) techniques, such as Machine Learning (ML) and Deep Learning (DL), hold promise in revolutionising dental diagnostics by improving accuracy and efficiency. Trained[…]

Elchaghaby, M., Aly, M. & Yousry, Y. Effectiveness of buccal infiltration anaesthesia compared to inferior alveolar nerve block anaesthesia in primary mandibular molar extractions: a randomised controlled study. Br Dent J (2023). Introduction The successful management of pain through local anaesthetic in dental treatment greatly impacts children’s perceptions of dental care. However, despite advancements in[…]

Ethical issues of artificial intelligence in medicine and healthcare. Farhud DD, Zokaei S. Iran J Public Health. 2021;50:0 Introduction The term “Artificial Intelligence (AI)” itself is quite broad in that it can be used to describe any piece of software or device with cognitive abilities; similar to those of humans. With the increasing prevalence of[…]

Duane, B., Croasdale, K., Ramasubbu, D. et al. Environmental sustainability: measuring and embedding sustainable practice into the dental practice. Br Dent J 226, 891–896 (2019). Background Sustainability within Dentistry is a key and current issue that needs to be addressed with climate change approaching faster than first predicted. International support is growing around this topic with the FDI recently[…]

Bhamra, I. B., Gallagher, J. E., Patel, R. (2023) ‘Telehealth technologies in care homes: a gap for dentistry?’, Journal of Public Health, fdad258 Introduction Care home residents are often individuals who require additional care and are dependent on others for carrying out activities of daily living. Studies have found that nursing homes do not prioritise[…]

Bhamra, I. B., Gallagher, J. E., Patel, R. (2023) ‘Telehealth technologies in care homes: a gap for dentistry?’, Journal of Public Health, fdad258 Introduction Care home residents are often individuals who require additional care and are dependent on others for carrying out activities of daily living. Studies have found that nursing homes do not prioritise[…]

Revilla-León, M., Gómez-Polo, M., Vyas, S., Barmak, B. A., Galluci, G. O., Att, W., & Krishnamurthy, V. R. (2023) ‘Artificial intelligence applications in implant dentistry: A systematic review’, The Journal of prosthetic dentistry, 129(2), pp. 293–300. INTRODUCTION Artificial intelligence (AI) research refers to development of computer systems displaying intelligent behaviour. Machine learning is a subtype[…]

Vuletić, M., Knežević, P., Jokić, D., Rebić, J., Žabarović, D., & Macan, D. (2014). Alveolar Bone Grafting in Cleft Patients from Bone Defect to Dental Implants. Acta stomatologica Croatica, 48(4), 250–257. Background Cleft lip and palate is the most prevalent congenital craniofacial deformity, which significantly impacts various aspects of life, including aesthetics, function, psychological well-being, dental development,[…]

Devlin, H., Williams, T., Graham, J. et al. The ADEPT study: a comparative study of dentists’ ability to detect enamel-only proximal caries in bitewing radiographs with and without the use of AssistDent artificial intelligence software. Br Dent J 231, 481–485 (2021). Background Picking up enamel-only caries using bitewing radiography is difficult and often missed by dental practitioners. This research[…]