Results 171 to 180 of about 42,337 (292)

Neutropenia (even mild) and anemia are poor prognostic factors in myelodysplastic syndromes. [PDF]

open access: yesFront Med (Lausanne)
Hausman R   +4 more
europepmc   +1 more source

Apoptosis Resistance of Blood Cells From Patients With Paroxysmal Nocturnal Hemoglobinuria, Aplastic Anemia, and Myelodysplastic Syndrome [PDF]

open access: bronze, 1997
Kentaro Horikawa   +6 more
openalex   +1 more source

Prognostic Impact of Cytomegalovirus Reactivation After Transplantation From Cord Blood Compared to Other Donor Sources in Patients With Adult T‐Cell Leukemia/Lymphoma in the Pre‐Letermovir Era

open access: yesTransplant Infectious Disease, EarlyView.
Cytomegalovirus reactivation (CMV‐react) is an indicator to predict the increased non‐relapse mortality and decreased overall survival in adult T‐cell leukemia‐lymphoma patients who received allogeneic transplantation from HLA‐matched related and unrelated donors.
Takuya Fukushima   +22 more
wiley   +1 more source

Advancements in genetic analysis: Insights from a case study and review of next‐generation sequencing techniques for veterinary oncology applications

open access: yesVeterinary Clinical Pathology, EarlyView.
Abstract Acute myeloid leukemia (AML) poses significant challenges in veterinary medicine, with limited treatment options and poor survival rates. While substantial progress has been made in characterizing human AML, translating these advancements to veterinary practice has been hindered by limited molecular understanding and diagnostic tools. The case
R. Adam Harris   +5 more
wiley   +1 more source

Characterization and Clinical Implications of p53 Dysfunction in Patients With Myelodysplastic Syndromes. [PDF]

open access: yesJ Clin Oncol
Zampini M   +50 more
europepmc   +1 more source

Artificial Intelligence in Veterinary Clinical Pathology—An Introduction and Review

open access: yesVeterinary Clinical Pathology, EarlyView.
ABSTRACT Artificial intelligence (AI), particularly through machine learning and deep learning, presents opportunities for the enhancement of the workflow of the veterinary clinical pathologist. This review introduces basic concepts in AI in a nontechnical manner and explores the qualification and integration of AI in veterinary clinical pathology. The
Samuel V. Neal   +2 more
wiley   +1 more source

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