Zwiri Abdalwhab, Jotish Ravi, Alam Mohammad Khursheed, Almuhanna Norah Khalid S, Alazmi Alanoud Mamluh, Noor Nor Farid Bin Mohd, Islam Mohammad Saiful
Faculty of Dentistry, Applied Sciences Private University, Amman, Jordan.
Endodontic Division, Restorative Dental Sciences, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia.
J Pharm Bioallied Sci. 2025 Jun;17(Suppl 2):S1270-S1272. doi: 10.4103/jpbs.jpbs_83_25. Epub 2025 Jun 18.
The integration of artificial intelligence (AI) in dentistry has transformed diagnostic accuracy and treatment planning. AI-powered tools have shown promise in enhancing risk assessment, enabling early identification of oral health conditions.
A prospective study was conducted to evaluate the efficiency of an AI-powered risk assessment tool. A total of 150 patients, aged 18-65 years, were included in the study. Patients underwent standard clinical examinations, followed by AI-based risk assessment using a machine learning platform trained on a dataset of 10,000 cases. The tool analyzed factors, such as oral hygiene habits, dietary patterns, and medical history, to generate individualized risk scores. Statistical analysis compared AI-generated risk assessments with those of dental experts to measure accuracy and reliability.
The AI tool demonstrated a sensitivity of 91% and a specificity of 88% in identifying high-risk cases. Of the 150 patients, 45 were identified as high risk, 70 as moderate risk, and 35 as low risk by the AI tool. Expert evaluation aligned with AI predictions in 92% of cases, confirming the tool's reliability. Time required for risk assessment was reduced by 40% compared to manual evaluations.
AI-powered tools offer significant advantages in general dentistry by improving the accuracy and efficiency of risk assessment. These tools can serve as valuable adjuncts to clinical expertise, enabling early interventions and personalized care strategies.
人工智能(AI)在牙科领域的整合改变了诊断准确性和治疗计划。人工智能驱动的工具在加强风险评估、实现口腔健康状况的早期识别方面已显示出前景。
进行了一项前瞻性研究,以评估一种人工智能驱动的风险评估工具的效率。共有150名年龄在18至65岁之间的患者纳入该研究。患者接受了标准临床检查,随后使用在10000例病例数据集上训练的机器学习平台进行基于人工智能的风险评估。该工具分析口腔卫生习惯、饮食模式和病史等因素,以生成个性化风险评分。统计分析将人工智能生成的风险评估与牙科专家的评估进行比较,以衡量准确性和可靠性。
该人工智能工具在识别高风险病例方面显示出91%的灵敏度和88%的特异性。在150名患者中,人工智能工具将45名识别为高风险,70名识别为中度风险,35名识别为低风险。专家评估在92%的病例中与人工智能预测一致,证实了该工具的可靠性。与人工评估相比,风险评估所需时间减少了40%。
人工智能驱动的工具通过提高风险评估的准确性和效率,在普通牙科中具有显著优势。这些工具可作为临床专业知识的宝贵辅助手段,实现早期干预和个性化护理策略。