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Hematologic Neoplasms

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Machine learning in paediatric haematological malignancies: a systematic review of prognosis, toxicity and treatment response models.

Pediatric research
BACKGROUND: Machine Learning (ML) has demonstrated potential in enhancing care in adult oncology. However, its application in paediatric haematological malignancies is still emerging, necessitating a comprehensive review of its capabilities and limit...

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...

Analysis of the Relationship Between and Cytokine Gene Expression in Hematological Malignancy: Leveraging Explained Artificial Intelligence and Machine Learning for Small Dataset Insights.

International journal of medical sciences
This study measures expression of () and related cytokine genes in bone marrow mononuclear cells in patients with hematological malignancies, analyzing the relationship between them with an integrated framework of statistical analyses, machine learn...

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

Cancer control : journal of the Moffitt Cancer Center
BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can lead to cardiovascular-related unplanned readmissions.ObjectiveWe aimed to develop a machine learnin...

Blood cancer prediction model based on deep learning technique.

Scientific reports
Blood cancer is among the critical health concerns among people around the world and normally emanates from genetic and environmental issues. Early detection becomes essential, as the rate of death associated with it is high, to ensure that the rate ...

Role of artificial intelligence in haematolymphoid diagnostics.

Histopathology
The advent of digital pathology and the deployment of high-throughput molecular techniques are generating an unprecedented mass of data. Thanks to advances in computational sciences, artificial intelligence (AI) approaches represent a promising avenu...

[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...

Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.

Transplant immunology
BACKGROUND: Allogeneic hematopoietic stem transplantation (allo-HSCT) constitutes a curative treatment for various hematological malignancies. However, various complications limit the therapeutic efficacy of this approach, increasing the morbidity an...

A novel method for screening malignant hematological diseases by constructing an optimal machine learning model based on blood cell parameters.

BMC medical informatics and decision making
BACKGROUND: Screening of malignant hematological diseases is of great importance for their diagnosis and subsequent treatment. This study constructed an optimal screening model for malignant hematological diseases based on routine blood cell paramete...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

BMC infectious diseases
OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematologic malignancies(HMs), particularly amid rising antibiotic resistance. This study aimed to analyze pathogen distribution, drug-resistance patterns and...