An improved data augmentation approach and its application in medical named entity recognition.

Performing data augmentation in medical named entity recognition (NER) is crucial due to the unique challenges posed by this field. Medical data is characterized by high acquisition costs, specialized terminology, imbalanced distributions, and limited training resources. These factors make achieving high performance in medical NER particularly difficult. Data augmentation methods help to mitigate these issues by generating additional training samples, thus balancing data distribution, enriching the training dataset, and improving model generalization. This paper proposes two data augmentation methods-Contextual Random Replacement based on Word2Vec Augmentation (CRR) and Targeted Entity Random Replacement Augmentation (TER)-aimed at addressing the scarcity and imbalance of data in the medical domain. When combined with a deep learning-based Chinese NER model, these methods can significantly enhance performance and recognition accuracy under limited resources. Experimental results demonstrate that both augmentation methods effectively improve the recognition capability of medical named entities. Specifically, the BERT-BiLSTM-CRF model achieved the highest F1 score of 83.587%, representing a 1.49% increase over the baseline model. This validates the importance and effectiveness of data augmentation in medical NER.

Management and monitoring recommendations for the use of eliglustat in adults with type 1 Gaucher disease in Europe.

PURPOSE: In Gaucher disease, diminished activity of the lysosomal enzyme, acid ß-glucosidase, leads to accumulation of glucosylceramides and related substrates, primarily in the spleen, liver, and bone marrow. Eliglustat is an oral substrate reduction therapy approved in the European Union and the United States as a first-line treatment for adults with type 1 Gaucher disease who have compatible CYP2D6 metabolism phenotypes. A European Advisory Council of experts in Gaucher disease describes the characteristics of eliglustat that are distinct from enzyme augmentation therapy (the standard of care) and miglustat (the other approved substrate reduction therapy) and recommends investigations and monitoring for patients on eliglustat therapy within the context of current recommendations for Gaucher disease management. RESULTS: Eliglustat is a selective, potent inhibitor of glucosylceramide synthase, the enzyme responsible for biosynthesis of glucosylceramides which accumulate in Gaucher disease. Extensive metabolism of eliglustat by CYP2D6, and, to a lesser extent, CYP3A of the cytochrome P450 pathway, necessitates careful consideration of the patient's CYP2D6 metaboliser status and use of concomitant medications which share metabolism by these pathways. Guidance on specific assessments and monitoring required for eliglustat therapy, including an algorithm to determine eligibility for eliglustat, are provided. CONCLUSIONS: As a first-line therapy for type 1 Gaucher disease, eliglustat offers eligible patients a daily oral therapy alternative to biweekly infusions of enzyme therapy. Physicians will need to carefully assess individual Gaucher patients to determine their appropriateness for eliglustat therapy. The therapeutic response to eliglustat and use of concomitant medications will require long-term monitoring.