ArticleAdvances in drug and alcohol research2024
K-nearest neighbor algorithm for imputing missing longitudinal prenatal alcohol data.
Article in Advances in drug and alcohol research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Decision-Support Framework for Nutritional Risk in Small Cell Lung Cancer: A Time-Series Model Using Imputation Strategies for Incomplete Clinical Data.Thoracic cancer · 2026Article
- Leveraging Machine Learning to Advance Alcohol Research: Current Applications, Challenges, and Opportunities.Alcohol research : current reviews · 2026Review
- Maternal obesity and prenatal alcohol exposure are associated with child development: Results from the Safe Passage Study.PloS one · 2026Article
- Development of a Composite Measure to Identify Priority Areas of Need for Cancer Screening Interventions.JCO clinical cancer informatics · 2025Article
- Prediction and optimization of electrochemical oxidation efficiency using machine learning: Insights from carbon-based anodes for water treatment.Journal of environmental management · 2025Article
- Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea).Frontiers in artificial intelligence · 2025Article
- Serotonergic receptor binding in the brainstem in the Sudden Infant Death Syndrome in a high-risk population.PloS one · 2025Article
- Prenatal risk factors for child executive function at 3-5 years of age: the roles of maternal mood, substance use, and socioeconomic adversity in a prospective cohort study.BMC pediatrics · 2024Article
- K-nearest neighbor algorithm for imputing missing longitudinal prenatal alcohol data.Advances in drug and alcohol research · 2024Article
- Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study.Journal of medical Internet research · 2023Article
- Prenatal smoking and drinking are associated with altered newborn autonomic functions.Pediatric research · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Aims: The objective of this study is to illustrate the application of a machine learning algorithm, K Nearest Neighbor ( Methods: We used data from the Safe Passage study (n = 11,083). Daily alcohol consumption for the last reported drinking day and 30 days prior was recorded using the Timeline Follow back method, which generated a variable amount of missing data per participants. Of the 3.2 million person-days of observation, data were missing for 0.36 million (11.4%). Using the Results: We found that data from 5 nearest neighbors (i.e., K = 5) and segments of 55 days provided imputed values with least imputation error. After deleting data segments from the first trimester data set with no missing days, there was no difference between actual and predicted values for 64% of deleted segments. For 31% of the segments, imputed data were within +/-1 drink/day of the actual. Imputation accuracy varied by study site because of the differences in the magnitude of drinking and proportion of missing data. Conclusion:
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.