109 citations · 188 across the 7 of their papers we have counts for
8 papers
"Where does it hurt?" -- Dataset and Study on Physician Intent Trajectories in Doctor Patient Dialogues
Tom Röhr, Soumyadeep Roy, Fares Al Mohamad +4
In a doctor-patient dialogue, the primary objective of physicians is to diagnose patients and propose a treatment plan. Medical doctors guide these conversations through targeted q…
Generalist embedding models are better at short-context clinical semantic search than specialized embedding models
Jean-Baptiste Excoffier, Tom Roehr, Alexei Figueroa +3
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. Their use in this highly criti…
MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou +6
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 fi…
MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain
Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann +12
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million Germ…
This Patient Looks Like That Patient: Prototypical Networks for Interpretable Diagnosis Prediction from Clinical Text
Betty van Aken, Jens-Michalis Papaioannou, Marcel G. Naik +4
The use of deep neural models for diagnosis prediction from clinical text has shown promising results. However, in clinical practice such models must not only be accurate, but prov…
Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Jens-Michalis Papaioannou, Paul Grundmann, Betty van Aken +5
Clinical phenotyping enables the automatic extraction of clinical conditions from patient records, which can be beneficial to doctors and clinics worldwide. However, current state-…
Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
Betty van Aken, Jens-Michalis Papaioannou, Manuel Mayrdorfer +3
Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities. We simulate patients at admission time, when decisi…
Canonical Trends: Detecting Trend Setters in Web Data
Felix Biessmann, Jens-Michalis Papaioannou, Mikio Braun +1
Much information available on the web is copied, reused or rephrased. The phenomenon that multiple web sources pick up certain information is often called trend. A central problem…