ReviewFrontiers in microbiology2019
Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease Outbreaks.
Review in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 56 citations in OpenAlex.
- Artificial Intelligence in Foodborne Pathogen Detection from Sensing to Food Safety Systems: A Systematic Review.Foods (Basel, Switzerland) · 2026Review
- Current and emerging molecular diagnostic approaches in the detection of human parasites.Parasitology research · 2026Review
- Application of Bioinformatics and Machine Learning Tools in Food Safety.Current nutrition reports · 2025Review
- Navigating the complex landscape of waterborne disease research.Journal of water and health · 2025Review
- Schistosomiasis transmission in Zimbabwe: Modelling based on machine learning.Infectious Disease Modelling · 2024Article
- Bridging Classical Methodologies inMicroorganisms · 2024Review
- Machine learning approach as an early warning system to prevent foodborne Salmonella outbreaks in northwestern Italy.Veterinary research · 2024Article
- Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.Microorganisms · 2024Review
- Knowledge, attitude, and practice toward foodborne disease among Chinese college students: a cross-sectional survey.Frontiers in public health · 2024Article
- Development and validation of a random forest algorithm for source attribution of animal and humanFrontiers in microbiology · 2023Article
- Genomics and pathotypes of the many faces of Escherichia coli.FEMS microbiology reviews · 2022Article
- Development of a Prediction Method of Cell Density in Autotrophic/Heterotrophic Microorganism Mixtures by Machine Learning Using Absorbance Spectrum Data.Biotech (Basel (Switzerland)) · 2022Article
- Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery Disease.Frontiers in microbiology · 2022Review
- Foodborne Disease Risk Prediction Using Multigraph Structural Long Short-term Memory Networks: Algorithm Design and Validation Study.JMIR medical informatics · 2021Article
- miRNA Regulatory Functions in Farm Animal Diseases, and Biomarker Potentials for Effective Therapies.International journal of molecular sciences · 2021Review
- Machine Learning Prediction of Foodborne Disease Pathogens: Algorithm Development and Validation Study.JMIR medical informatics · 2021Article
- NGS read classification using AI.PloS one · 2021Article
- Typing methods based on whole genome sequencing data.One health outlook · 2020Review
- Advances in Microbial Diagnostics: Machine Learning and Nanotechnology for Zoonotic Disease Control.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Foodborne diseases (FBDs) are infections of the gastrointestinal tract caused by foodborne pathogens (FBPs) such as bacteria [
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.