Page 1 | Search Results | Blood | American Society of Hematology

Skip Nav Destination

1-13 of 13

Sort by

Sort Order Select

Journal Articles

Explainable End-to-End Supervised Learning Identifies Myelodysplastic Neoplasms in Bone Marrow Smears

Jan-Niklas Eckardt, Tim Schmittmann, Freya Schulze, Sebastian Riechert, Martin M. K. Schneider, Lukas Reichel, Miriam Eva Helena Gediga, Katja Sockel, Anas Shekh Sulaiman, Ekaterina Balaian, Christoph Röllig, Frank P. Kroschinsky, Anne Marie Asemissen, Uwe Platzbecker, Christian Pohlkamp, Torsten Haferlach, Karsten Wendt, Martin Bornhäuser, Jan Moritz Middeke

Blood (2023) 142 (Supplement 1): 2269.

https://doi.org/10.1182/blood-2023-185628

Published: 2023

Journal Articles

Automated Cytomorphological Analysis of Bone Marrow Samples: A Proof-of-Principle Study for AI-Based Classification on a Real-Life Data Set of 979 Unselected Cases

Christoph Kornauth, Valerio Lupperger, Sven Maschek, Wolfgang Kern, Claudia Haferlach, Torsten Haferlach, Christian Pohlkamp

Blood (2023) 142 (Supplement 1): 2284.

https://doi.org/10.1182/blood-2023-188716

Published: 2023

Journal Articles

Genomic Landscape of Ccus Compared to MDS Indicates a Potential Applicability of the IPSS-M

Sandra Huber, Constance Regina Baer, Stephan Hutter, Gregor Hoermann, Christian Pohlkamp, Wencke Walter, Manja Meggendorfer, Wolfgang Kern, Torsten Haferlach, Claudia Haferlach

Blood (2023) 142 (Supplement 1): 4609.

https://doi.org/10.1182/blood-2023-177582

Published: 2023

Journal Articles

Proposal ofmyeloid Neoplasms with MYC -Positive Double Minutes As a Distinct Entity

Isolde Summerer, Wencke Walter, Manja Meggendorfer, Torsten Haferlach, Frank Dicker, Stephan Hutter, Niroshan Nadarajah, Constance Regina Baer, Anna Stengel, Wolfgang Kern, John M. Bennett, Claudia Haferlach, Christian Pohlkamp

Blood (2023) 142 (Supplement 1): 2930.

https://doi.org/10.1182/blood-2023-189902

Published: 2023

Journal Articles

Modification of the ELN Classification 2022 Refines Risk Assessment in MDS/AML Patients

Sandra Huber, Constance Regina Baer, Stephan Hutter, Frank Dicker, Irene Fuhrmann, Manja Meggendorfer, Christian Pohlkamp, Wolfgang Kern, Torsten Haferlach, Claudia Haferlach, Gregor Hoermann

Blood (2023) 142 (Supplement 1): 61.

https://doi.org/10.1182/blood-2023-179822

Published: 2023

Journal Articles

Machine Learning Algorithm Correctly Identifies 95% of Cells in Differential Count of Blood Smears: A Prospective Study on >29,000 Cases and >17 Million Single Cells

Torsten Haferlach, Niroshan Nadarajah, Claudia Haferlach, Wolfgang Kern, Christian Pohlkamp

Blood (2022) 140 (Supplement 1): 1909–1910.

https://doi.org/10.1182/blood-2022-165863

Published: 2022

Journal Articles

A Fully Automated Digital Workflow for Assessment of Bone Marrow Cytomorphology Based on Single Cell Detection and Classification with AI

Christian Pohlkamp, Niroshan Nadarajah, Piyush Srivastava, Sven Maschek, Rudolf Drescher, Siegfried Hänselmann, Thomas Lörch, Claudia Haferlach, Wolfgang Kern, Torsten Haferlach

Blood (2022) 140 (Supplement 1): 10725–10726.

https://doi.org/10.1182/blood-2022-168780

Published: 2022

Journal Articles

AML and MDS Classification According to Who 2022 and International Consensus Classification: Do We Invent a Babylonian Confusion of Languages?

Sandra Huber, Constance Baer, Stephan Hutter, Frank Dicker, Manja Meggendorfer, Christian Pohlkamp, Wolfgang Kern, Torsten Haferlach, Claudia Haferlach, Gregor Hoermann

Blood (2022) 140 (Supplement 1): 555–556.

https://doi.org/10.1182/blood-2022-162326

Published: 2022

Journal Articles

A Completely Digital Workflow for Differentials in Bone Marrow Cytomorphology Supported By Machine Learning Provides Promising Results in Object Detection

Christian Pohlkamp, Niroshan Nadarajah, Inseok Heo, Dimitros Tziotis, Sven Maschek, Rudolf Drescher, Siegfried Hänselmann, Thomas Lörch, Claudia Haferlach, Wolfgang Kern, Torsten Haferlach

Blood (2021) 138 (Supplement 1): 4922.

https://doi.org/10.1182/blood-2021-152851

Published: 2021

Journal Articles

Automated Peripheral Blood Cell Differentiation Using Artificial Intelligence - a Study with More Than 10,000 Routine Samples in a Specialized Leukemia Laboratory

Torsten Haferlach, Christian Pohlkamp, Inseok Heo, Rudolf Drescher, Siegfried Hänselmann, Thomas Lörch, Wolfgang Kern, Claudia Haferlach, Niroshan Nadarajah

Blood (2021) 138 (Supplement 1): 103.

https://doi.org/10.1182/blood-2021-152447

Published: 2021

Journal Articles

Whole Genome Sequencing Identifies Non- KIT Mutations and Cytogenetic Aberrations in Systemic Mastocytosis but Has Limited Sensitivity for Detection of KIT D816V

Gregor Hoermann, Manja Meggendorfer, Constance Baer, Heiko Müller, Wencke Walter, Stephan Hutter, Christian Pohlkamp, Niroshan Nadarajah, Wolfgang Kern, Torsten Haferlach, Claudia Haferlach

Blood (2021) 138 (Supplement 1): 1495.

https://doi.org/10.1182/blood-2021-152956

Published: 2021

Journal Articles

Putative Germline Variants in the Predisposition Genes DDX41 , ETV6 and GATA2 investigated in 1,228 Patients with Sporadic AML or MDS

Anna Maierhofer, PhD, Constance Baer, PhD, Christian Pohlkamp, MD, Manja Meggendorfer, PhD, Wolfgang Kern, MD, Claudia Haferlach, MD, Torsten Haferlach, MD

Blood (2020) 136 (Supplement 1): 17–18.

https://doi.org/10.1182/blood-2020-140742

Published: 2020

Journal Articles

Machine Learning (ML) Can Successfully Support Microscopic Differential Counts of Peripheral Blood Smears in a High Throughput Hematology Laboratory

Christian Pohlkamp, MD, Kapil Jhalani, Niroshan Nadarajah, Inseok Heo, PhD, William Wetton, Rudolf Drescher, PhD, Siegfried Hänselmann, PhD, Thomas Lörch, PhD, Claudia Haferlach, MD, Wolfgang Kern, MD, Torsten Haferlach, MD

Blood (2020) 136 (Supplement 1): 45–46.

https://doi.org/10.1182/blood-2020-140215

Published: 2020

NARROW

Explainable End-to-End Supervised Learning Identifies Myelodysplastic Neoplasms in Bone Marrow Smears

Automated Cytomorphological Analysis of Bone Marrow Samples: A Proof-of-Principle Study for AI-Based Classification on a Real-Life Data Set of 979 Unselected Cases

Genomic Landscape of Ccus Compared to MDS Indicates a Potential Applicability of the IPSS-M

Proposal ofmyeloid Neoplasms with MYC -Positive Double Minutes As a Distinct Entity

Modification of the ELN Classification 2022 Refines Risk Assessment in MDS/AML Patients

Machine Learning Algorithm Correctly Identifies 95% of Cells in Differential Count of Blood Smears: A Prospective Study on >29,000 Cases and >17 Million Single Cells

A Fully Automated Digital Workflow for Assessment of Bone Marrow Cytomorphology Based on Single Cell Detection and Classification with AI

AML and MDS Classification According to Who 2022 and International Consensus Classification: Do We Invent a Babylonian Confusion of Languages?

A Completely Digital Workflow for Differentials in Bone Marrow Cytomorphology Supported By Machine Learning Provides Promising Results in Object Detection

Automated Peripheral Blood Cell Differentiation Using Artificial Intelligence - a Study with More Than 10,000 Routine Samples in a Specialized Leukemia Laboratory

Whole Genome Sequencing Identifies Non- KIT Mutations and Cytogenetic Aberrations in Systemic Mastocytosis but Has Limited Sensitivity for Detection of KIT D816V

Putative Germline Variants in the Predisposition Genes DDX41 , ETV6 and GATA2 investigated in 1,228 Patients with Sporadic AML or MDS

Machine Learning (ML) Can Successfully Support Microscopic Differential Counts of Peripheral Blood Smears in a High Throughput Hematology Laboratory

Email alerts

ASH Publications

American Society of Hematology

Email alerts

ASH Publications

American Society of Hematology

This Feature Is Available To Subscribers Only