This work presents results for a dataset with Brazilian Portuguese clinical notes. We develop and optimize a Logistic Regression model, a Convolutional Neural Network (CNN), a Gated Recurrent Unit Neural Network and a CNN with Attention (CNN-Att) for prediction of diagnosis ICD codes. We also ...
networkstomodelthesemanticrelationshipsbetweenmedicaltermsandextractfeaturesfromclinicaltext.Themodelwastrainedonalargedatasetofclinicalrecordsandachievedstate-of-the-artperformanceontheICD-10codepredictiontask.Theproposedmethodcanbeusedtoautomatetheprocessofclinicalcoding,improvetheaccuracyofICDcoding,andreducethework...
metadata data cancer germany open-data dataset classification deutschland icd krebs rki zfkd klassifikationen 65c Updated Jan 26, 2024 StefanoTrv / SimpleICD10-Java-edition Star 5 Code Issues Pull requests Discussions A simple Java library for ICD-10 codes java icd-10 icd10 icd icd-codes...
This framework is applied to the extensive and publicly available MIMIC-III dataset, enabling us to leverage both numerical and text-based data for improved ICD-9 code prediction. Our system uses text representation models to understand the text-based medical records; the Gated Recurrent Unit (...
for fuwai dataset and increased it by 20 each time. for codiesp dataset, we let \(f_s\) take 40, 60, 80, 100, and 140 respectively footnote 6 . for each of the thresholds, the number of the qualified codes and selected records, and the proportion of the total code occurrences ...
dataset of first opinion clinical free-text narratives on a simultaneous training task of Masked Language (MLM) and Next Sentence Prediction (NSP), mimicking the tasks used in the initial pre-training of BERT12. For MLM training, 15% of the words within a given clinical narrative were masked...
For each dataset, we ranked the codes by their frequencies in descending order, and plotted the frequencies against the rankings (Fig. 3). Apparently, the distributions of the code frequencies in both datasets follow long-tail distribution. Figure 4 shows the 10 most frequent codes and their fr...
The results show that, for the I2B2 2010 challenge dataset, the method can improve the performance of the named entity recognition (NER) task. Chen, et al. (2021) [19] used a deep learning model for ICD-10 coding, to find the diagnosis and corresponding procedure codes on medical text....
The results show that, for the I2B2 2010 challenge dataset, the method can improve the performance of the named entity recognition (NER) task. Chen, et al. (2021) [19] used a deep learning model for ICD-10 coding, to find the diagnosis and corresponding procedure codes on medical text....
In reference to Table 1, we summarize the performance of work on ICD code prediction. It seems that the accuracy of our work is not as high as the previous work. However, in this study, we have the dataset containing 2017 distinct ICD-9 codes, which is more than those in previous ...