Trials

Trials and primary studies

Every primary study the non-Cochrane dental caries reviews include, resolved to one record per study so a trial included by several reviews is counted once. Most are randomized trials; aetiology and diagnostic reviews also include observational and accuracy studies.

Primary studies
5,083
2,113 PMID · 1,332 DOI · 1,638 author and year
In two or more reviews
277
overlap between reviews
Trial PICO extracted
0
extraction not run yet
Per-trial results
0
extraction not run yet
Limit the list

16 studies, most shared first

StudyYearReviewsOutcome linksTrial PICO
Caries Risk Prediction Models in a Medical Health Care Setting.
Kalhan 2020 · Kalhan T A, Un Lam C, et al. · Journal of dental research
PMID:32311276
202021not extracted yet
Early Childhood Predictors for Dental Caries: A Machine Learning Approach.
Toledo Reyes (2023) · Toledo Reyes L, Knorst J K, et al. · Journal of dental research
PMID:37246832
20231none statednot extracted yet
Prediction model of dental caries in 12-year-old children in Sichuan Province based on machine learning.
Xinmiao 2023 · Yan Xinmiao, Sun Taolan, et al. · Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
PMID:38597034
20231none statednot extracted yet
Prediction model for early childhood caries risk based on behavioral determinants using a machine learning algorithm
Qu 2022 · Qu Xing, Zhang Chao, et al. · Computer Methods and Programs in Biomedicine
DOI:10.1016/j.cmpb.2022.107221
202211not extracted yet
Identifying high-risk children for dental caries in school settings: A simple predictive model
Wickramasinghe 2022 · Wickramasinghe Danushi, Usgodaarachchi Udaya · Ceylon Medical Journal
DOI:10.4038/cmj.v67i4.9744
202211not extracted yet
Prediction model for early childhood caries risk based on behavioral determinants using a machine learning algorithm.
Qu (2022) · Qu Xing, Zhang Chao, et al. · Computer methods and programs in biomedicine
PMID:36384058
202211not extracted yet
Identifying high-risk children for dental caries in school settings: A simple predictive model.
Wickramasinghe (2022) · Wickramasinghe Danushi, Usgodaarachchi Udaya · The Ceylon medical journal
PMID:38421295
20221none statednot extracted yet
Prediction Models of Early Childhood Caries Based on Machine Learning Algorithms.
Park 2021 · Park You-Hyun, Kim Sung-Hwa, et al. · International journal of environmental research and public health
PMID:34444368
20211none statednot extracted yet
A predictive nomogram: a cross-sectional study on a simple-to-use model for screening 12-year-old children for severe caries in middle schools.
Duan 2021 · Duan Shaoying, Li Meng, et al. · BMC oral health
PMID:34544417
202111not extracted yet
Nomogram prediction of caries risk among schoolchildren age 7 years based on a cohort study in Shanghai.
Luo 2021 · Luo Yuan, Zhang Hao, et al. · The Journal of international medical research
PMID:34851774
202111not extracted yet
Simplified Prediction Model for Accurate Assessment of Dental Caries Risk among Participants Aged 10-18 Years.
Kim (2018) · Kim Jung-Min, Choi Jun-Seon, et al. · The Tohoku journal of experimental medicine
PMID:30333362
201811not extracted yet
A Comparative Study of Machine Learning Techniques for Caries Prediction
Montenegro 2008 · Montenegro Robson D., Oliveira Adriano L. I., et al. · 2008 20th IEEE International Conference on Tools with Artificial Intelligence
DOI:10.1109/ictai.2008.138
20081none statednot extracted yet
25-Hydroxyvitamin D3 metabolism in a human leukemia cell line.
Yaxuan 2023 · Bar-Shavit Z, Horst R L, et al. · Calcified tissue international
PMID:3102023
198611not extracted yet
Kalhan 2020
DOI:10.1177/0022034520913032
NR1none statednot extracted yet
Toledo Reyes 2023
DOI:10.1177/00220345231170537
NR1none statednot extracted yet
Kim 2018
DOI:10.1620/tjem.246.8
NR11not extracted yet