ArticleInternational journal of environmental research and public health2021
The Comprehensive Machine Learning Analytics for Heart Failure.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 17 citations in OpenAlex.
- Integrated transcriptomics and machine learning reveal diagnostic biomarkers and immune-stromal remodeling in ischemic heart failure.Frontiers in bioinformatics · 2026Article
- Article
- Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters.Frontiers in cardiovascular medicine · 2025Article
- Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.Scientific reports · 2024Article
- Understanding Arteriosclerotic Heart Disease Patients Using Electronic Health Records: A Machine Learning and Shapley Additive exPlanations Approach.Healthcare informatics research · 2023Article
- Risk prediction of heart failure in patients with ischemic heart disease using network analytics and stacking ensemble learning.BMC medical informatics and decision making · 2023Article
- Prediction and Analysis of Heart Failure Decompensation Events Based on Telemonitored Data and Artificial Intelligence Methods.Journal of cardiovascular development and disease · 2023Article
- Predicting Six-Month Re-Admission Risk in Heart Failure Patients Using Multiple Machine Learning Methods: A Study Based on the Chinese Heart Failure Population Database.Journal of clinical medicine · 2023Article
- Fibroblast growth factor 21 in heart failure.Heart failure reviews · 2023Review
- Improving predictive performance in incident heart failure using machine learning and multi-center data.Frontiers in cardiovascular medicine · 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
3 authors at 1 institution in 1 country.
Funding
Abstract
PubMed holds no abstract for this paper.
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.