Inteligencia artificial en la evaluación y manejo de pacientes con epilepsia.
Bibliographic record
Abstract
La epilepsia es una enfermedad que frecuentemente conlleva significativos niveles de morbi-mortalidad, afecta seriamente la calidad de vida y, en cerca de un tercio de los pacientes, es refractaria a diversos tratamientos. La inteligencia artificial (IA) ha beneficiado el estudio, tratamiento y pronóstico de los pacientes con epilepsia a través de los años. Estos logros abarcan diagnóstico, predicción de crisis automatizada, monitoreo avanzado de crisis epilépticas y electroencefalograma, uso de recursos genéticos en manejo y diagnóstico, algoritmos en imagen y tratamiento, neuromodulación y cirugía robótica. La presente revisión explica de forma práctica los avances actuales y futuros de la inteligencia artificial, rama de la ciencia que ha mostrado resultados prometedores en el diagnóstico y tratamiento de pacientes con epilepsia.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".