Munich Leukemia Laboratory (Germany)

An overview and a roadmap for artificial intelligence in hematology and oncology

Wiebke Rösler, Michael Altenbuchinger, Bettina Baeßler et al.

2023 · 78 Zit.

How artificial intelligence might disrupt diagnostics in hematology in the near future

Wencke Walter, Claudia Haferlach, Niroshan Nadarajah et al.

2021 · 72 Zit.

Artificial intelligence in hematology

Aziz Nazha, Olivier Elemento, Sanjay Ahuja et al.

2025 · 8 Zit.

AML diagnostics in the 21st century: Use of AI

Torsten Haferlach, Jan‐Niklas Eckardt, Wencke Walter et al.

2025 · 8 Zit.

Translating the regulatory landscape of medical devices to create fit‐for‐purpose artificial intelligence (<scp>AI</scp>) cytometry solutions

Goce Bogdanoski, Fabienne Lucas, Wolfgang Kern et al.

2024 · 7 Zit.

Human and artificial intelligence to illuminate MDS

Torsten Haferlach

2020 · 4 Zit.

How I read an article that uses machine learning methods

Aziz Nazha, Olivier Elemento, Shannon K. McWeeney et al.

2023 · 3 Zit.

The “<i>David Vs Goliath</i>” Study: Application of Large Language Models (LLM) for Automatic Medical Information Retrieval from Multiple Data Sources to Accelerate Clinical and Translational Research in Hematology

Mattia Delleani, Saverio D’Amico, Elisabetta Sauta et al.

2024 · 1 Zit.

Artificial intelligence for risk assessment and outcome prediction in malignant haematology

Jan‐Niklas Eckardt, Wencke Walter, Jan Moritz Middeke et al.

2025 · 1 Zit.

AI in Diagnostics

Torsten Haferlach

2024 · 0 Zit.

Evaluating large language models in real-world hematologic clinical decision-making: Performance, limitations, and clinical implications

David M. Swoboda, Amy E. DeZern, James T. England et al.

2025 · 0 Zit.

Artificial intelligence‑driven virtual tumor board enhances precision care in myelodysplastic syndromes (MDS)

David M. Swoboda, Amy E. DeZern, James T. England et al.

2025 · 0 Zit.

Unlocking new frontiers in leukemia diagnostics through large language Model–Driven report generation

Vivian Wuerf, Christopher Maier, Benjamin Braun et al.

2025 · 0 Zit.

Automated multi-source data consensus classification of low-frequency variants in hematologic malignancies using transparent artificial intelligence

Niroshan Nadarajah, Nanditha Mallesh, Kathrin Hildebrand et al.

2025 · 0 Zit.