Trial reportComputational and mathematical methods in medicine2022
Risk Prediction of Coronary Artery Stenosis in Patients with Coronary Heart Disease Based on Logistic Regression and Artificial Neural Network.
Trial report in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 16 citations in OpenAlex.
- Metoprolol-spironolactone combination for coronary heart disease with concurrent heart failure: impact on cardiac function.American journal of translational research · 2026Article
- Comparing the Performances of Support Vector Machines and Artificial Neural Networks for Predicting Coronary Artery Diseases: A Cross-Sectional Study.Cardiology research and practice · 2026Article
- Expression of Serum Ferritin, Human neutrophil lipocalin, Procalcitonin, and inflammatory factors in children with Kawasaki disease and their relationship to coronary artery lesions.American journal of translational research · 2025Article
- Article
- Advanced detection of coronary artery disease via deep learning analysis of plasma cytokine data.Frontiers in cardiovascular medicine · 2024Article
- Tongue color parameters in predicting the degree of coronary stenosis: a retrospective cohort study of 282 patients with coronary angiography.Frontiers in cardiovascular medicine · 2024Article
- Establishment and analysis of artificial neural network diagnosis model for coagulation-related molecular subgroups in coronary artery disease.Frontiers in genetics · 2024Article
- Predicting the risk of acute kidney injury after cardiopulmonary bypass: development and assessment of a new predictive nomogram.BMC anesthesiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Coronary heart disease (CHD) is considered an inflammatory relative disease. This study is aimed at analyzing the health information of serum interferon in CHD based on logistic regression and artificial neural network (ANN) model. Method: A total of 155 CHD patients diagnosed by coronary angiography in our department from January 2017 to March 2020 were included. All patients were randomly divided into a training set ( Result: The Spearman correlation analysis showed that the degree of stenosis was positively correlated with serum IFN- Conclusion: The logistic regression model and ANN model have similar predictive performance for coronary artery stenosis risk factors in patients with CHD. In patients with CHD, the expression levels of IFN-
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.