AkshatSurolia
ICD 10 Code Prediction
The Publicly Available Clinical BERT Embeddings paper contains four unique clinicalBERT models: initialized with BERT-Base (casedL-12H-768A-12) or BioBERT (BioBERT-Base v1.0 + PubMed 200K + PMC 270K) & trained on either all MIMIC notes or only discharge summaries. from transformers import AutoTokenizer, BertForSequenceClassification tokenizer = AutoTokenizer.frompretrained("AkshatSurolia/ICD-10-Code-Prediction") model = BertForSequenceClassification.frompretrained("AkshatSurolia/ICD-10-Code-Prediction") config = model.config text = "subarachnoid hemorrhage scalp laceration service: surgery major surgical or invasive" encodedinput = tokenizer(text, returntensors='pt') output = model(encodedinput) results = output.logits.detach().cpu().numpy()[0].argsort()[::-1][:5] return [ config.id2label[ids] for ids in results]