Search Results for author:
Found 6 papers, 4 papers with code
Generalist embedding models are better at short-context clinical semantic search than specialized embedding models
The increasing use of tools and solutions based on Large Language Models (LLMs) for various tasks in the medical domain has become a prominent trend.
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.
This Patient Looks Like That Patient: Prototypical Networks for Interpretable Diagnosis Prediction from Clinical Text
The use of deep neural models for diagnosis prediction from clinical text has shown promising results.
Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Clinical phenotyping enables the automatic extraction of clinical conditions from patient records, which can be beneficial to doctors and clinics worldwide.
Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities.
Ranked #1 on
Medical Diagnosis
on Clinical Admission Notes from MIMIC-III
(using extra training data)
