Validation of a Machine Learning Model to Predict Childhood Lead Poisoning-Reference-Cited by-同舟云学术

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Validation of a Machine Learning Model to Predict Childhood Lead Poisoning

Published:2020-09-16 Issue:9 Volume:3 Page:e2012734
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Potash Eric¹,Ghani Rayid²,Walsh Joe¹,Jorgensen Emile³,Lohff Cortland⁴,Prachand Nik³,Mansour Raed³

Affiliation:

1. Harris School of Public Policy, University of Chicago, Chicago, Illinois

2. Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania

3. Chicago Department of Public Health, Chicago, Illinois

4. Southern Nevada Health District, Las Vegas

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2770650/potash_2020_oi_200483_1599661889.87241.pdf

Reference31 articles.

1. Continual decrease in blood lead level in Americans: United States National Health Nutrition and Examination Survey 1999-2014.;Tsoi;Am J Med,2016

2. NTP monograph on health effects of low-level lead.;National Toxicology Program;NTP Monogr,2012

3. Effect of chelation therapy on the neuropsychological and behavioral development of lead-exposed children after school entry.;Dietrich;Pediatrics,2004

4. Prevention of childhood lead toxicity.;Council on Environmental Health;Pediatrics,2016

5. Mapping for prevention: GIS models for directing childhood lead poisoning prevention programs.;Miranda;Environ Health Perspect,2002

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1. Predicting blood lead in uruguayan children: Individual- vs neighborhood-level ensemble learners;PLOS Global Public Health;2024-09-04

2. Construction of a machine learning-based prediction model for unfavorable discharge outcomes in patients with ischemic stroke;Heliyon;2024-09

3. When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes;ACM Journal on Responsible Computing;2024-08-22

4. Estimated Childhood Lead Exposure From Drinking Water in Chicago;JAMA Pediatrics;2024-05-01

5. Prediction the prognosis of the poisoned patients undergoing hemodialysis using machine learning algorithms;BMC Medical Informatics and Decision Making;2024-02-06

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