AIMC Topic: Hematologic Diseases
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DeepHeme, a high-performance, generalizable deep ensemble for bone marrow morphometry and hematologic diagnosis.
Science translational medicine
Jun 11, 2025
Cytomorphological analysis of the bone marrow aspirate (BMA) is pivotal for the diagnostic workup of a broad range of hematological disorders. However, this skill is error prone, highly complex, and time consuming. Deep learning-based models for the ...
A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.
Turkish journal of medical sciences
Mar 27, 2025
BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual microscopy diagnostics for blood cell disorders. Nowadays, data-driven artificial intelligence (AI) techniques open new perspectives in digital hemat...
Recognition of Genetic Conditions After Learning With Images Created Using Generative Artificial Intelligence.
JAMA network open
Mar 4, 2024
IMPORTANCE: The lack of standardized genetics training in pediatrics residencies, along with a shortage of medical geneticists, necessitates innovative educational approaches.
Next generation phenotyping for diagnosis and phenotype-genotype correlations in Kabuki syndrome.
Scientific reports
Jan 28, 2024
The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photog...
Biophysical Profiling of Sickle Cell Disease Using Holographic Cytometry and Deep Learning.
International journal of molecular sciences
Jul 25, 2023
Sickle cell disease (SCD) is an inherited hematological disorder associated with high mortality rates, particularly in sub-Saharan Africa. SCD arises due to the polymerization of sickle hemoglobin, which reduces flexibility of red blood cells (RBCs),...
Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.
Cells
Jun 30, 2023
Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the development of computational programs that can mimic human intelligence. In particular, machine learning and deep learning models have enabled the identifi...
A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.
Scientific reports
Jan 21, 2022
Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system...
Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.
International journal of molecular sciences
Mar 27, 2020
Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection ...
Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.
Scientific reports
Apr 15, 2019
We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n...
Artificial intelligence and machine learning in haematology.
British journal of haematology
Feb 6, 2019
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