AIMC Topic: Hematologic Neoplasms
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From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.
International journal of molecular sciences
Jun 1, 2025
Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies. Bispecific antibodies (BsAbs), which redirect cytotoxic T cells toward malignant targets via dual antigen engagement, are now established components ...
Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends.
TheScientificWorldJournal
May 18, 2025
The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major and emerging subjects that lie at the intersection of artificial intelligence and medical research. This survey systematically examines the state-of-t...
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
Apr 17, 2025
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...
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
Apr 13, 2025
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...
Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.
Expert review of anti-infective therapy
Apr 4, 2025
INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in patients with hematologic malignancies and hematopoietic stem cell transplant (HSCT) recipients, the increasing prevalence of antimicrobial resistance...
Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.
BMC infectious diseases
Mar 26, 2025
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...
Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.
Transplant immunology
Feb 26, 2025
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
Feb 11, 2025
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...
Blood cancer prediction model based on deep learning technique.
Scientific reports
Jan 13, 2025
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
Oct 22, 2024
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...
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