Multi-Label Classification Of Biomedical Texts
4 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Label Classification Of Biomedical Texts
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MIMIC-III
Most implemented papers
ML-Net: multi-label classification of biomedical texts with deep neural networks
Due to this nature, the multi-label text classification task is often considered to be more challenging compared to the binary or multi-class text classification problems.
MIMIC-III, a freely accessible critical care database
MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital.
An Empirical Evaluation of Deep Learning for ICD-9 Code Assignment using MIMIC-III Clinical Notes
lsy3/clinical-notes-diagnosis-dl-nlp
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Conclusion: A set of standard metrics was utilized in assessing the performance of ICD-9 code assignment on MIMIC-III dataset.
Predicting Multiple ICD-10 Codes from Brazilian-Portuguese Clinical Notes
ICD coding from electronic clinical records is a manual, time-consuming and expensive process.
