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Hematologic Neoplasms

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Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Advancing diagnostic testing capabilities such as clinical next generation sequencing methods offer the potential to diagnose, risk stratify, and guide specialized treatment, but must be balanced against the escalating costs of healthcare to identify...

Augmented Human Intelligence and Automated Diagnosis in Flow Cytometry for Hematologic Malignancies.

American journal of clinical pathology
OBJECTIVES: Clinical flow cytometry is laborious, time-consuming, and expensive given the need for data review by highly trained personnel such as technologists and pathologists as well as the significant number of normal cases. Given these issues, a...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

International journal of hematology
This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose methotrexate (HD-MTX) based on machine learning. A total of 205 patients were recruited. Five variables ...

Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

International journal of laboratory hematology
Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and engineers have strived to refine the acquisition and display of the electronic signals generated. A large a...

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model.

Scientific reports
Blood cancer has been a growing concern during the last decade and requires early diagnosis to start proper treatment. The diagnosis process is costly and time-consuming involving medical experts and several tests. Thus, an automatic diagnosis system...

Therapy resistance mechanisms in hematological malignancies.

International journal of cancer
Hematologic malignancies are model diseases for understanding neoplastic transformation and serve as prototypes for developing effective therapies. Indeed, the concept of systemic cancer therapy originated in hematologic malignancies and has guided t...

An AI-Aided Diagnostic Framework for Hematologic Neoplasms Based on Morphologic Features and Medical Expertise.

Laboratory investigation; a journal of technical methods and pathology
A morphologic examination is essential for the diagnosis of hematological diseases. However, its conventional manual operation is time-consuming and laborious. Herein, we attempt to establish an artificial intelligence (AI)-aided diagnostic framework...

AMLnet, A deep-learning pipeline for the differential diagnosis of acute myeloid leukemia from bone marrow smears.

Journal of hematology & oncology
Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of bone marrow smears based on the French-American-British (FAB) classification system remains an essential criterion in the diagnosis of hematological m...

Advances in next-generation sequencing and emerging technologies for hematologic malignancies.

Haematologica
Innovations in molecular diagnostics have often evolved through the study of hematologic malignancies. Examples include the pioneering characterization of the Philadelphia chromosome by cytogenetics in the 1970s, the implementation of polymerase chai...