<scp>ICD</scp> coding for epilepsy: Past, present, and future—A report by the International League Against Epilepsy Task Force on <scp>ICD</scp> codes in epilepsy
Bibliographic record
Abstract
The World Health Organization (WHO) International Classification of Diseases (ICD) has been used to classify causes of morbidity and mortality such as epilepsy for more than 50 years. The aims of this critical commentary are to do the following: (1) Introduce the ICD classification, summarize the ICD-9 and ICD-10 codes for epilepsy and seizures, and discuss the challenges of mapping epilepsy codes between these two versions; (2) discuss how the ICD-9 and ICD-10 relate to the revised International League Against Epilepsy (ILAE) terminology and concepts for classification of seizures and epilepsies; (3) discuss how ICD-coded data have been used for epilepsy care and research and briefly examine the potential impact of the international ICD-10 clinical modifications on research; (4) discuss the upcoming ICD-11 codes and the role of the epilepsy community in their development; and (5) discuss how the ICD-11 will conform more closely to the current ILAE terminology and classification of the epilepsies and seizures and its potential impact on clinical care, surveillance, and public health and research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".