Patients' perspectives on the use of artificial intelligence in dentistry: a regional survey

Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists

OBJECTIVES

This study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists.

METHODS

A total of 272 completed questionnaires were included in this study. In the first part of the study, approval was obtained from the patients, and data were collected about their socio-demographic characteristics. In the second part the 11-item Dentist Trust Scale was applied. In the third and fourth parts, there were questions about two clinical scenarios, the patients' knowledge of attitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performed using a Likert-type scale. Data were analyzed with the Chi-square, one-way ANOVA, and ordinal logistic regression tests (p < 0.05).

RESULTS

The patients believed that "AI is useful" (3.86 ± 1.03) and were not afraid of the use of AI in dentistry (2.40 ± 1.05). Educational level was considerably related to the patients' attitudes to the use of AI for dental diagnostics (p < 0.05). The patients stated that "dentists are extremely thorough and careful" (4.39 ± 0.77).

CONCLUSIONS

The patients displayed a positive attitude to AI-based diagnosis in the dental field and appear to exhibit trust in dentists. The use of Al in routine clinical practice can provide important benefit to physicians as a clinical decision support system in dentistry and understanding patients' attitudes may allow dentists to shape AI-supported dentistry in the future.

Acceptability of artificial intelligence in dental radiology among patients in India: are we ready for this revolution?

OBJECTIVE

In recent times, artificial Intelligence (AI) has gained popularity in medical as well as dental radiology. Studies have been conducted among medical and dental students and professionals about the knowledge and understanding towards AI. The aim of this study was to investigate the perceptions and acceptability of AI in dental radiology among a group of Indian patients seeking dental treatment.

METHODS

A cross-sectional research was planned with a validated questionnaire, containing ten close ended questions amongst 1562 patients. Their sociodemographic characters, opinions and attitudes regarding AI and feasibility of acceptance of AI-based dental radiological diagnosis among patients was evaluated. The study sample was divided in various groups on the basis of their age; group-1(16-30 years), group-2(31-45 years) and group-3(>45 years), educational status and urban/rural background. Statistical analysis was done by Chi-square test with significance value set at p< 0.005.

RESULTS-

The participants possessed impressive knowledge about AI. Patients' awareness, attitudes and acceptability towards AI for dental radiographic diagnosis were substantially influenced by age, education level and residential background. Although many of them, especially the urban and more educated participants believed that AI could be more accurate, they preferred the human judgement. Overall, a negative attitude in terms of acceptability of AI in dental radiology was observed in this study.

CONCLUSIONS

Participants opined that AI should only be used as an auxiliary tool and valued clinical judgment over AI in ambiguous situations. It is recommended that this promising technological advancement can be used for initial screening in dental radiology.

Obstacles behind the innovation- a peek into Artificial intelligence in the field of orthodontics - A Literature review

This article explores the potential benefits of Artificial Intelligence (AI) and Machine Learning (ML) in Orthodontics, highlighting their efficiency and accuracy. While AI has influenced various fields, its application in orthodontics is just being explored. With the innovation comes challenges that are associated with AI. This article emphasizes the documented role of AI and its associated barriers in Orthodontics.

Methods

Literature research is performed in data sources like online library journals PubMed and MEDLINE, NIH (National Institute of Health), Science Direct, WILEY online library, and ORAL HEALTH GROUP, among others. Our review was carried out on articles published to date.

Conclusion

The findings in this review highlight the considerable promise of employing AI within orthodontics. However, the emergence of AI also brings forth fresh challenges that must be considered. Striking a balance between innovation and addressing these challenges is crucial for advancing orthodontics.

Artificial intelligence and personalized diagnostics in periodontology: A narrative review

Periodontal diseases pose a significant global health burden, requiring early detection and personalized treatment approaches. Traditional diagnostic approaches in periodontology often rely on a "one size fits all" approach, which may overlook the unique variations in disease progression and response to treatment among individuals. This narrative review explores the role of artificial intelligence (AI) and personalized diagnostics in periodontology, emphasizing the potential for tailored diagnostic strategies to enhance precision medicine in periodontal care. The review begins by elucidating the limitations of conventional diagnostic techniques. Subsequently, it delves into the application of AI models in analyzing diverse data sets, such as clinical records, imaging, and molecular information, and its role in periodontal training. Furthermore, the review also discusses the role of research community and policymakers in integrating personalized diagnostics in periodontal care. Challenges and ethical considerations associated with adopting AI-based personalized diagnostic tools are also explored, emphasizing the need for transparent algorithms, data safety and privacy, ongoing multidisciplinary collaboration, and patient involvement. In conclusion, this narrative review underscores the transformative potential of AI in advancing periodontal diagnostics toward a personalized paradigm, and their integration into clinical practice holds the promise of ushering in a new era of precision medicine for periodontal care.

Perceptiveness and Attitude on the use of Artificial Intelligence (AI) in Dentistry among Dentists and Non-Dentists - A Regional Survey

Artificial intelligence (AI) is an emerging tool in modern medicine and the digital world. AI can help dentists diagnose oral diseases, design treatment plans, monitor patient progress and automate administrative tasks. The aim of this study is to evaluate the perception and attitude on use of artificial intelligence in dentistry for diagnosis and treatment planning among dentists and non-dentists' population of south Tamil Nadu region in India.

Materials and Methods

A cross sectional online survey conducted using 20 close ended questionnaire google forms which were circulated among the dentists and non -dentists population of south Tamil Nadu region in India. The data collected from 264 participants (dentists -158, non-dentists -106) within a limited time frame were subjected to descriptive statistical analysis.

Results

70.9% of dentists are aware of artificial intelligence in dentistry. 40.5% participants were not aware of AI in caries detection but aware of its use in interpretation of radiographs (43.9%) and in planning of orthognathic surgery (42.4%) which are statistically significant P < 0.05.44.7% support clinical experience of a human doctor better than AI diagnosis. Dentists of 54.4% agree to support AI use in dentistry.

Conclusion

The study concluded AI use in dentistry knowledge is more with dentists and perception of AI in dentistry is optimistic among dentists than non -dentists, majority of participants support AI in dentistry as an adjunct tool to diagnosis and treatment planning.

Accuracy of Treatment Recommendations by Pragmatic Evidence Search and Artificial Intelligence: An Exploratory Study

There is extensive literature emerging in the field of dentistry with the aim to optimize clinical practice. Evidence-based guidelines (EBGs) are designed to collate diagnostic criteria and clinical treatment for a range of conditions based on high-quality evidence. Recently, advancements in Artificial Intelligence (AI) have instigated further queries into its applicability and integration into dentistry. Hence, the aim of this study was to develop a model that can be used to assess the accuracy of treatment recommendations for dental conditions generated by individual clinicians and the outcomes of AI outputs. For this pilot study, a Delphi panel of six experts led by CoTreat AI provided the definition and developed evidence-based recommendations for subgingival and supragingival calculus. For the rapid review-a pragmatic approach that aims to rapidly assess the evidence base using a systematic methodology-the Ovid Medline database was searched for subgingival and supragingival calculus. Studies were selected and reported based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), and this study complied with the minimum requirements for completing a restricted systematic review. Treatment recommendations were also searched for these same conditions in ChatGPT (version 3.5 and 4) and Bard (now Gemini). Adherence to the recommendations of the standard was assessed using qualitative content analysis and agreement scores for interrater reliability. Treatment recommendations by AI programs generally aligned with the current literature, with an agreement of up to 75%, although data sources were not provided by these tools, except for Bard. The clinician's rapid review results suggested several procedures that may increase the likelihood of overtreatment, as did GPT4. In terms of overall accuracy, GPT4 outperformed all other tools, including rapid review (Cohen's kappa 0.42 vs. 0.28). In summary, this study provides preliminary observations for the suitability of different evidence-generating methods to inform clinical dental practice.

Glimpse into the future of prosthodontics: The synergy of artificial intelligence

Prosthodontics, deals in the restoration and replacement of missing and structurally compromised teeth, this field has been remarkably transformed in the last two decades. Through the integration of digital imaging and three-dimensional printing, prosthodontics has evolved to provide more durable, precise, and patient-centric outcome. However, as we stand at the convergence of technology and healthcare, a new era is emerging, one that holds immense promise for the field and that is artificial intelligence (AI). In this paper, we explored the fascinating challenges and prospects associated with the future of prosthodontics in the era of AI.