# Medical Text Processing

This is a Bert model optimized for Italian, specifically designed for COVID-19-related text classification tasks.

A biomedical named entity recognition model fine-tuned based on microsoft/biogpt

DeepSeek-R1 is an improved version based on the deepseek-ai foundation model, specializing in audio-to-text transcription tasks and supporting English language processing.

BERT-based Arabic sentence embedding model supporting semantic text similarity tasks

XLM-RoBERTa-based German emotion classification model capable of recognizing 28 emotions

This is a clinical note summarization model fine-tuned based on the T5-small model, primarily used for generating summaries of clinical notes.

A medical domain Q&A model fine-tuned based on TinyLlama-1.1B-Chat-v1.0, optimized for medical texts and Q&A scenarios

TinySapBERT is a compact biomedical entity representation model trained on the SapBERT framework, specifically designed for biomedical named entity recognition tasks.

A RoBERTa-based temporal named entity recognition model for Spanish clinical trial texts, designed to detect temporal expressions and age entities.

A model fine-tuned based on BioBERT, specifically designed to identify and remove mentions of past medical history from radiology reports.

A biomedical domain Q&A model fine-tuned based on BioBERT-v1.1

A T5-small summarization model fine-tuned for Indonesian language, based on huseinzol05's t5-small-bahasa-summarization-cased model and fine-tuned using the indosum dataset.