Work

AI-powered precision: Unmasking hidden treatment optimizations for lower-risk myelodysplastic syndrome patients based on real-world, multi center EHR data.

Year: 2025

Type: conference-abstract

Source: Blood

DOI: 10.1182/blood-2025-6209

Authors: Marek Dudziński, Anna Lason, Arkadiusz Sycz, Patryk Weglarz, Natalia Leonczuk, Lukasz Szukalski, Szymon Fornagiel, Grzegorz Helbig, Jaroslaw Piszcz, Marta Sobas, Agnieszka Pluta, Krzysztof Madry, Łukasz Brodowski, Grzegorz Basak, Michal J. Dabrowski, Karol Lis

Institutions: University of Rzeszów, Medical University of Silesia, Medical University of Białystok, Nicolaus Copernicus University, Collegium Medicum in Bydgoszcz, Medical University of Warsaw, Institute of Computer Science, Polish Academy of Sciences

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4417012715

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