AIMC Topic: Hematologic Neoplasms

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[Advancements in artificial intelligence for the precise diagnosis and treatment of hematological malignancies].

Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi
Hematological malignancy is a highly heterogeneous disease with complex biological characteristics and diverse clinical manifestations. Therefore, precise diagnosis and treatment are crucial and urgently needed. To further improve the accuracy of dia...

Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis.

Cancer discovery
Clonal hematopoiesis (CH) is a phenomenon of clonal expansion of hematopoietic stem cells driven by somatic mutations affecting certain genes. Recently, CH has been linked to the development of hematologic malignancies, cardiovascular diseases, and o...

A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment.

Studies in health technology and informatics
Enabling patients to actively document their health information significantly improves understanding of how therapies work, disease progression, and overall life quality affects for those living with chronic disorders such as hematologic malignancies...

An Integral R-Banded Karyotype Analysis System of Bone Marrow Metaphases Based on Deep Learning.

Archives of pathology & laboratory medicine
CONTEXT.—: Conventional karyotype analysis, which provides comprehensive cytogenetic information, plays a significant role in the diagnosis and risk stratification of hematologic neoplasms. The main limitations of this approach include long turnaroun...

[Flow cytometry increases the proportion of valuable samples in cerebrospinal fluid with normal cell count in malignant blood diseases].

Revista medica de Chile
BACKGROUND: The alteration of cerebrospinal fluid (CSF) in hematologic neoplasms is a poor prognostic marker. The characteristics of CSF are usually analyzed by flow cytometry or cytology. However, paucicellular CSF samples (≤5 cells/dL) can sometime...

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...

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...

Machine learning in haematological malignancies.

The Lancet. Haematology
Machine learning is a branch of computer science and statistics that generates predictive or descriptive models by learning from training data rather than by being rigidly programmed. It has attracted substantial attention for its many applications i...