The Integration of Salivary pH Meters and Artificial Intelligence in the Early Diagnosis and Management of Dental Caries in Pediatric Dentistry: A Scoping Review

Oral, Год журнала: 2025, Номер 5(1), С. 12 - 12

Опубликована: Фев. 10, 2025

Dental caries is one of the most prevalent chronic conditions among children globally. Salivary pH monitoring, an essential diagnostic parameter, plays a critical role in understanding risk and oral health. This scoping review aims to evaluate application digital salivary meters pediatric dentistry, particularly diagnosis prevention, while exploring potential integration artificial intelligence (AI) this domain. Methods: A literature search was conducted across PubMed, Web Science, Scopus databases for studies published between 2014 2024. The inclusion criteria focused on clinical involving aged 1 18 years use meters. Studies that utilized AI conjunction with monitoring were also reviewed. Data extracted analyzed assess effectiveness detection their broader health applications. Results: Out 549 articles screened, 11 met criteria. highlighted utility assessing risk, dietary impacts, evaluating preventive treatments. However, none combined AI. Emerging technologies, such as smartphone-based sensors, have demonstrated promising applications real-time, non-invasive diagnostics. Conclusions: Digital provide precise reproducible measurements, significantly enhancing assessment strategies dentistry. While remains unexplored context, its refine prediction models personalize treatments underscores need future research area. These advancements could improve prevention management, outcomes.

Язык: Английский

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Efficient and Accurate pH Determination with pH Test Strips Based on Machine Learning

Analytical Chemistry, Год журнала: 2024, Номер 96(28), С. 11498 - 11507

Опубликована: Июль 1, 2024

The determination of pH values is crucial in various fields, such as analytical chemistry, medical diagnostics, and biochemical research. test strips, renowned for their convenience cost-effectiveness, are commonly utilized qualitative estimation. Recently, quantitative methods determining using strips have been developed. However, these can be prone to errors due environmental factors, lighting conditions, which affect the imaging quality strips. To address challenges, we developed an innovative approach that combines machine learning techniques with values. Our method involves extracting artificial features from strip images combining them across multiple dimensions comprehensive analysis. ensure optimal feature selection, a selection strategy based on SHAP importance. This helps identifying most relevant contribute accurate prediction. Furthermore, integrated algorithms, employing robust stacking fusion establish highly reliable value prediction model. proposed automates through effectively overcoming limitations associated interference. Experimental results demonstrate this convenient, effective,

Язык: Английский

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Smartphone-based pH titration for liquid food applications

Chemical Papers, Год журнала: 2024, Номер unknown

Опубликована: Сен. 28, 2024

Язык: Английский

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Immunochromatographic POC-CCA Test for the diagnosis of intestinal schistosomiasis in a high endemic region in Brazil: Differences in the interpretation of results

Acta Tropica, Год журнала: 2024, Номер 254, С. 107181 - 107181

Опубликована: Март 17, 2024

Язык: Английский

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