ArticleHeliyon2023
Automated ICD coding for coronary heart diseases by a deep learning method.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recent Advances in AI for Automated ICD Coding: A Systematic Literature Review.Journal of medical systems · 2026Pooled it
- Using Medical Named Entity Recognition in Automatic ICD Prediction.BioMed research international · 2025Article
- A review of evaluation approaches for explainable AI with applications in cardiology.Artificial intelligence review · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated ICD coding via machine learning that focuses on some specific diseases has been a hot topic. As one of the leading causes of death, coronary heart diseases (CHD) have seldom been specifically studied by related research, probably due to lack of data concretely targeting at the diseases. Based on Fuwai-CHD and MIMIC-III-CHD, which are a private dataset from Fuwai Hospital and the CHD-related subset of a public dataset named MIMIC-III respectively, this study aimed at automated CHD coding by a deep learning method, which mainly consists of three modules. The first is a
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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.