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- - -Redefining innovation at DFKI-SLT, where cutting-edge research meets real-world impact.
- - -Discover the talented individuals who bring brilliance and innovation to our projects.
- -Senior Researcher
- -Senior Researcher
- -Senior Researcher
- -Post-doctoral Researcher
- -PhD Candidate
- -PhD Candidate
- -PhD Candidate
- -Area of Work
-Area of Work
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-Area of Work
-Area of Work
-Area of Work
-Area of Work
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-Area of Work
-Explore our cutting-edge research projects in AI and NLP, driving innovation in healthcare.
- - -MEDINYM aims to build patient trust and promote data-driven healthcare initiatives, setting new standards in the field.
-Innovating healthcare through AI-driven solutions for better patient outcomes.
-Exploring ethical AI applications in diverse fields such as education and finance.
-Developing tools to enhance multilingual communication through AI-powered platforms.
-Using AI for predictive analytics in climate change research and mitigation strategies.
-Using AI for predictive analytics in climate change research and mitigation strategies.
-Using AI for predictive analytics in climate change research and mitigation strategies.
-Developing tools to enhance multilingual communication through AI-powered platforms.
-Developing tools to enhance multilingual communication through AI-powered platforms.
-A brief description of Project C.
-Access meticulously curated datasets to fuel your experiments and discoveries.
-Interact with our state-of-the-art tools and experience real-world applications.
- -Access open-source tools, libraries, and codebases for advanced research and development.
-Efficient tools to enhance machine learning model performance.
- Download Tool -- Discover the latest insights and findings in AI and NLP from our research group. -
- -- Overview of the 9th Social Media Mining for Health Applications (#SMM4H) Shared Tasks at ACL 2024 – Large Language Models and Generalizability for Social Media NLP. - (Xu et al., SMM4H 2024) -
- Read Paper -- Overview of #SMM4H 2024 – Task 2: Cross-Lingual Few-Shot Relation Extraction for Pharmacovigilance in French, German, and Japanese. - (Raithel et al., SMM4H@ACL 2024) -
- Read Paper -- Improving Self-training with Prototypical Learning for Source-Free Domain Adaptation on Clinical Text. - (Shimizu et al., BioNLP@ACL, 2024) -
- Read Paper -- Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates. - (MacPhail et al., BioNLP@ACL, 2024) -
- Read Paper -- DFKI-NLP at SemEval-2024 Task 2: Towards Robust LLMs Using Data Perturbations and MinMax Training. - (Verma & Raithel, SemEval@NAACL) -
- Read Paper -- A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages. - (Raithel* & Yeh* et al., LREC-COLING, 2024) -
- Read Paper -- Assessing Authenticity and Anonymity of Synthetic User-generated Content in the Medical Domain. - (Nishiyama* & Raithel* et al., CALDPseudo@EACL, 2024) -
- Read Paper -- Investigating the Impact of AI on Shared Decision-Making in Post-Kidney Transplant Care (PRIMA-AI): - Protocol for a Randomized Controlled Trial. (Osmanodja et al., JMIR Research Protocols) -
- Read Paper -- XAI for Better Exploitation of Text in Medical Decision Support. - (Ravichandran et al., BioNLP) -
- Read Paper -- Prospectively Investigating the Impact of AI on Shared Decision Making in Post-Kidney Transplant Care (PRIMA-AI): - Protocol for a Longitudinal Qualitative Study. (Sassi et al., BMJ Open) -
- Read Paper -- The Influence of Artificial Intelligence on Shared Decision Making in Nephrology. - (Samhammer et al., The Digitalization of Healthcare for Older Adults) -
- Read Paper -- Retrieval-Augmented Knowledge Integration into Language Models: A Survey. - (Chen et al., KnowledgeLM) -
- Read Paper -- Towards ML-Supported Triage Prediction in Real-World Emergency Room Scenarios. - (Maschhur et al., BioNLP) -
- Read Paper -- Dynamic Prompting: Large Language Models for Task-Oriented Dialog. - (Nehring et al., CLiC-it) -
- Read Paper -- Findings of the WMT 2024 Biomedical Translation Shared Task: Test Sets on Abstract Level. - (Neves et al., WMT24) -
- Read Paper -- Large Language Models for Clinical Text Cleansing: Enhance Medical Concept Normalization. - (Abdulnazar et al., IEEE Access) -
- Read Paper -- Vital Sign Forecasting in Perioperative Patients in General Wards. - (Mosch et al., The Digitalization of Healthcare for Older Adults) -
- Read Paper -- Unsupervised SapBERT-based Bi-Encoders for Medical Concept Annotation: Clinical Narratives with SNOMED CT. - (Abdulnazar et al., Sage Digital Health) -
- Read Paper -- Technology in Healthcare: Introduction, Clinical Impacts, Workflow Improvement, Structuring and Assessment. - (Pickering et al., Now Publishers, Inc.) -
- Read Paper -Transforming knowledge into inspiration through cutting-edge courses and engaging sessions in NLP and AI.
- Winter Semester
- Place: TU Berlin (Quality & Usability Lab)
Topic | -Student | -Supervisor | -Type | -
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A Systematic Literature Review of De-identification and Anonymization of Clinical Texts | -Karina Baikova | -Ibrahim Baroud & Lisa Raithel | -Bachelor's | -
Multimodal Explanations for Clinical Decision Support Systems | -Fares Guermazi | -Ajay Ravichandran & Lisa Raithel | -Master's | -
tbd | -Emilia Schulenburg | -Lisa Raithel & Prof. Markus Feufel | -Master's | -
tbd | -Farez Maschhur | -Roland Roller | -Master's | -
tbd | -Iyadh Ben Cheikh Larbi | -Roland Roller | -Master's | -
tbd | -Ammer Ayach | -Roland Roller | -Master's | -
topic | -Maxim Wölk | -Ibrahim Baroud & Roland Roller | -Bachelor's | -
Topic | -Student | -Supervisor | -Type | -
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Data Generation in Benchmarking Models for Detecting Adverse Drug Effects | -Dorothea MacPhail | -David Harbecke & Lisa Raithel & Prof. Manfred Stede | -Master's | -
Analysing Robustness of Large Language Models and Data Variability | -Bhuvanesh Verma | -Lisa Raithel & Prof. Manfred Stede | -Master's | -
Automatic Summarization for Long Biomedical Documents | -Chung-Fan Tsai | -Lisa Raithel & Prof. Manfred Stede | -Individual Module | -
Enhancing the Information Extraction from Clinical Trials with Large Language Models | -Jasper Julius Spierling | -Roland Roller & Yuxuan Chen | -Master's | -
Improving Runtime Efficiency in Transformer-based Language Models for Relation Extraction in the Biomedical Domain | -Clara Wicharz | -Philippe Thomas | -Master's | -
Grounding of free-text gene mutation descriptions | -Hugo Alejandro Robalino Urvina | -Philippe Thomas | -Master's | -
Leveraging Large Language Models for Cyber Grooming Chats Generation | -Yulia Constien | -Philippe Thomas | -Master's | -
Evaluating the Detection of Adverse Drug Effects | -Dorothea MacPhail | -David Harbecke & Lisa Raithel & Prof. Manfred Stede | -Individual Module | -
Medical Concept Normalization in a Low-Resource Setting | -Tim Patzelt | -Lisa Raithel & Prof. Manfred Stede | -Master's | -
Transformer-based Relation Extraction of Variant-Phenotype Associations | -Yusra Seyam | -Lisa Raithel & Philippe Thomas | -Master's | -
Unlock your academic potential! Explore our curated list of open thesis opportunities. Collaborate with leading experts and take the next step in your academic journey.
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