The Potential Promise of Machine Learning in Myelodysplastic Syndrome
V Visconte, JP Maciejewski, L Guarnera - Seminars in Hematology, 2024 - Elsevier
The introduction of artificial intelligence (AI), and in particular machine learning (ML), has
revolutionized biomedical research at the clinical level, a trend that also includes …
revolutionized biomedical research at the clinical level, a trend that also includes …
Integrating AI and ML in Myelodysplastic Syndrome Diagnosis: State-of-the-Art and Future Prospects
AM Elshoeibi, A Badr, B Elsayed, O Metwally… - Cancers, 2023 - mdpi.com
Simple Summary This paper aims to highlight the latest advancements in the application of
artificial intelligence in the diagnosis of myelodysplastic syndrome. This research focuses on …
artificial intelligence in the diagnosis of myelodysplastic syndrome. This research focuses on …
Prevalence of massively diluted bone marrow cell samples aspirated from patients with myelodysplastic syndromes (MDS) or suspected of MDS: A retrospective …
K Ogata, Y Mochimaru, N Kasai, K Sei… - British Journal of …, 2024 - Wiley Online Library
Bone marrow (BM) examination is a key element in the diagnosis and prognostic grading of
myelodysplastic syndromes (MDSs), and obtaining adequate BM cell samples is critical for …
myelodysplastic syndromes (MDSs), and obtaining adequate BM cell samples is critical for …
Revisiting the most often used item in the haematological tool box—The extent of haemodilution in bone marrow aspirates
P Hokland - British Journal of Haematology, 2024 - Wiley Online Library
In this issue, a nationwide retrospective Japanese study finds that, in a second opinion
setting, one‐third of bone marrow aspirates from patients suspected of myelodysplastic …
setting, one‐third of bone marrow aspirates from patients suspected of myelodysplastic …
The role of flow cytometry in the classification of myeloid disorders
L Saft - Die Pathologie, 2023 - Springer
Abstract The World Health Organization classification (WHO-HAEM5) and the International
Consensus Classification (ICC 2022) of myeloid neoplasms are based on the integration of …
Consensus Classification (ICC 2022) of myeloid neoplasms are based on the integration of …
[HTML][HTML] Challenging the status flow: how artificial intelligence is advancing diagnosis of myelodysplastic neoplasms
C Duetz, TM Westers, AA Van de Loosdrecht - Haematologica, 2023 - ncbi.nlm.nih.gov
Over the past few years, artificial intelligence (AI) has begun to fulfill its promise of
revolutionizing healthcare. In this issue of Haematologica, Clichet and colleagues describe …
revolutionizing healthcare. In this issue of Haematologica, Clichet and colleagues describe …
Enhancing chromosomal analysis efficiency through deep learning-based artificial intelligence graphic analysis
Y Zhou, L Xu, L Zhang, D Shi, C Wu, R Wei… - Discover Applied …, 2024 - Springer
The objective of this study is to evaluate the efficacy and diagnostic utility of an advanced
chromosomal analysis approach. A total of 2663 amniotic fluid samples were chosen for …
chromosomal analysis approach. A total of 2663 amniotic fluid samples were chosen for …
[PDF][PDF] Artificial intelligence-based Myelodysplastic Syndromes Score, 2022 classifications, and the Molecular International Prognostic Scoring System: a perfect match
V Clichet, T Boyer - Haematologica, 2020 - haematologica.org
Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms,
characterized by ineffective hematopoiesis leading to cytopenias, dysplastic features in …
characterized by ineffective hematopoiesis leading to cytopenias, dysplastic features in …