Search Results - "Roller, Roland"

Large Language Models for Clinical Text Cleansing Enhance Medical Concept Normalization by Abdulnazar, Akhila, Roller, Roland, Schulz, Stefan, Kreuzthaler, Markus

“…Most clinical information is only available as free text. Large language models (LLMs) are increasingly applied to clinical data to streamline communication,…”
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When performance is not enough-A multidisciplinary view on clinical decision support by Roller, Roland, Burchardt, Aljoscha, Samhammer, David, Ronicke, Simon, Duettmann, Wiebke, Schmeier, Sven, Möller, Sebastian, Dabrock, Peter, Budde, Klemens, Mayrdorfer, Manuel, Osmanodja, Bilgin

“…Scientific publications about the application of machine learning models in healthcare often focus on improving performance metrics. However, beyond often…”
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Prospectively investigating the impact of AI on shared decision-making in post kidney transplant care (PRIMA-AI): protocol for a longitudinal qualitative study among patients, their support persons and treating physicians at a tertiary care centre by Sassi, Zeineb, Eickmann, Sascha, Roller, Roland, Osmanodja, Bilgin, Burchardt, Aljoscha, Samhammer, David, Dabrock, Peter, Möller, Sebastian, Budde, Klemens, Herrmann, Anne

“…IntroductionAs healthcare is shifting from a paternalistic to a patient-centred approach, medical decision making becomes more collaborative involving…”
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Use and accuracy of decision support systems using artificial intelligence for tumor diseases: a systematic review and meta-analysis by Oehring, Robert, Ramasetti, Nikitha, Ng, Sharlyn, Roller, Roland, Thomas, Philippe, Winter, Axel, Maurer, Max, Moosburner, Simon, Raschzok, Nathanael, Kamali, Can, Pratschke, Johann, Benzing, Christian, Krenzien, Felix

“…Background For therapy planning in cancer patients multidisciplinary team meetings (MDM) are mandatory. Due to the high number of cases being discussed and…”
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Concordance of a decision algorithm and multidisciplinary team meetings for patients with liver cancer—a study protocol for a randomized controlled trial by Ng, Sharlyn S. T, Oehring, Robert, Ramasetti, Nikitha, Roller, Roland, Thomas, Philippe, Chen, Yuxuan, Moosburner, Simon, Winter, Axel, Maurer, Max-Magnus, Auer, Timo A, Kamali, Can, Pratschke, Johann, Benzing, Christian, Krenzien, Felix

“…Abstract Introduction Multidisciplinary team meetings (MDMs), also known as tumor conferences, are a cornerstone of cancer treatments. However, barriers such…”
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Editorial: Information extraction for health documents by Mensa, Enrico, Martínez Fernández, Paloma, Roller, Roland, Radicioni, Daniele P

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"Nothing works without the doctor:" Physicians' perception of clinical decision-making and artificial intelligence by Samhammer, David, Roller, Roland, Hummel, Patrik, Osmanodja, Bilgin, Burchardt, Aljoscha, Mayrdorfer, Manuel, Duettmann, Wiebke, Dabrock, Peter

“…Artificial intelligence-driven decision support systems (AI-DSS) have the potential to help physicians analyze data and facilitate the search for a correct…”
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SIA: a scalable interoperable annotation server for biomedical named entities by Kirschnick, Johannes, Thomas, Philippe, Roller, Roland, Hennig, Leonhard

“…Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume. Extraction of specific information from these…”
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Evaluation of a clinical decision support system for detection of patients at risk after kidney transplantation by Roller, Roland, Mayrdorfer, Manuel, Duettmann, Wiebke, Naik, Marcel G, Schmidt, Danilo, Halleck, Fabian, Hummel, Patrik, Burchardt, Aljoscha, Möller, Sebastian, Dabrock, Peter, Osmanodja, Bilgin, Budde, Klemens

“…Patient care after kidney transplantation requires integration of complex information to make informed decisions on risk constellations. Many machine learning…”
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Investigating the Impact of AI on Shared Decision-Making in Post-Kidney Transplant Care (PRIMA-AI): Protocol for a Randomized Controlled Trial by Osmanodja, Bilgin, Sassi, Zeineb, Eickmann, Sascha, Hansen, Carla Maria, Roller, Roland, Burchardt, Aljoscha, Samhammer, David, Dabrock, Peter, Möller, Sebastian, Budde, Klemens, Herrmann, Anne

“…Patients after kidney transplantation eventually face the risk of graft loss with the concomitant need for dialysis or retransplantation. Choosing the right…”
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Unsupervised -based bi-encoders for medical concept annotation of clinical narratives with SNOMED CT by Akhila Abdulnazar, Roland Roller, Stefan Schulz, Markus Kreuzthaler

“…Objective Clinical narratives provide comprehensive patient information. Achieving interoperability involves mapping relevant details to standardized medical…”
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Unsupervised SapBERT -based bi-encoders for medical concept annotation of clinical narratives with SNOMED CT by Abdulnazar, Akhila, Roller, Roland, Schulz, Stefan, Kreuzthaler, Markus

“…Objective Clinical narratives provide comprehensive patient information. Achieving interoperability involves mapping relevant details to standardized medical…”
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eHealth in transplantation by Duettmann, Wiebke, Naik, Marcel G, Zukunft, Bianca, Osmonodja, Bilgin, Bachmann, Friederike, Choi, Mira, Roller, Roland, Mayrdorfer, Manuel, Halleck, Fabian, Schmidt, Danilo, Budde, Klemens

“…eHealth ("electronic" Health) is a new field in medicine that has the potential to change medical care, increase efficiency, and reduce costs. In this review,…”
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SapBERT-Based Medical Concept Normalization Using SNOMED CT by Abdulnazar, Akhila, Kreuzthaler, Markus, Roller, Roland, Schulz, Stefan

“…Word vector representations, known as embeddings, are commonly used for natural language processing. Particularly, contextualized representations have been…”
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EffiCare: Better Prognostic Models via Resource-Efficient Health Embeddings by Rethmeier, Nils, Serbetci, Necip Oguz, Möller, Sebastian, Roller, Roland

“…Recent medical prognostic models adapted from high data-resource fields like language processing have quickly grown in complexity and size. However, since…”
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Prospectively investigating the impact of AI onshared decision-making in post kidney transplant care (PRIMA-AI): protocol for a longitudinal qualitative study among patients, their support persons and treating physicians at a tertiary care centre by Sassi, Zeineb, Eickmann, Sascha, Roller, Roland, Osmanodja, Bilgin, Burchardt, Aljoscha, Samhammer, David, Dabrock, Peter, Möller, Sebastian, Budde, Klemens, Herrmann, Anne

“…As healthcare is shifting from a paternalistic to a patient-centred approach, medical decision making becomes more collaborative involving patients, their…”
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When performance is not enough-A multidisciplinary view on clinical decision support by Roland Roller, Aljoscha Burchardt, David Samhammer, Simon Ronicke, Wiebke Duettmann, Sven Schmeier, Sebastian Möller, Peter Dabrock, Klemens Budde, Manuel Mayrdorfer, Bilgin Osmanodja

“…Scientific publications about the application of machine learning models in healthcare often focus on improving performance metrics. However, beyond often…”
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Automatic Extraction of Medication Mentions from Tweets—Overview of the BioCreative VII Shared Task 3 Competition by Weissenbacher, Davy, O’Connor, Karen, Rawal, Siddharth, Zhang, Yu, Tsai, Richard Tzong-Han, Miller, Timothy, Xu, Dongfang, Anderson, Carol, Liu, Bo, Han, Qing, Zhang, Jinfeng, Kulev, Igor, Köprü, Berkay, Rodriguez-Esteban, Raul, Ozkirimli, Elif, Ayach, Ammer, Roller, Roland, Piccolo, Stephen, Han, Peijin, Vydiswaran, V G Vinod, Tekumalla, Ramya, Banda, Juan M, Bagherzadeh, Parsa, Bergler, Sabine, Silva, João F, Almeida, Tiago, Martinez, Paloma, Rivera-Zavala, Renzo, Wang, Chen-Kai, Dai, Hong-Jie, Alberto Robles Hernandez, Luis, Gonzalez-Hernandez, Graciela

“…Abstract This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter…”
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Detecting biomedical relations using distant supervision by Roller, Roland

“…This work concerns the detection of relationships between key information in biomedical publications, such as treatments for diseases or side-effects of drugs…”
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Factuality Detection using Machine Translation -- a Use Case for German Clinical Text by Sumait, Mohammed Bin, Gabryszak, Aleksandra, Hennig, Leonhard, Roller, Roland

“…Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present,…”
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