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Found 7 papers, 1 papers with code
Is Open-Source There Yet? A Comparative Study on Commercial and Open-Source LLMs in Their Ability to Label Chest X-Ray Reports
While recent publications have explored GPT-4 in its application to extracting information of interest from radiology reports, there has not been a real-world comparison of GPT-4 to different leading open-source models.
Medical Foundation Models are Susceptible to Targeted Misinformation Attacks
We validate our findings in a set of 1, 038 incorrect biomedical facts.
MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields.
MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain.
What Does DALL-E 2 Know About Radiology?
Generative models such as DALL-E 2 could represent a promising future tool for image generation, augmentation, and manipulation for artificial intelligence research in radiology provided that these models have sufficient medical domain knowledge.
3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware
Our model performed comparable to previously published 3D U-Net architectures, achieving a mean Dice score of 0. 679 on the tuning dataset, 0. 648 on the Coronacases dataset and 0. 405 on the MosMed dataset.
Comparing Different Deep Learning Architectures for Classification of Chest Radiographs
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research.
