Hematology

Leukemia

Latest AI and machine learning research in leukemia for healthcare professionals.

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Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.

AIM: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause som...

Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines.

Mechanobiological measurements have the potential to discriminate healthy cells from pathological ce...

Application of artificial intelligence in chronic myeloid leukemia (CML) disease prediction and management: a scoping review.

BACKGROUND: Navigating the complexity of chronic myeloid leukemia (CML) diagnosis and management pos...

Machine learning to predict completion of treatment for pancreatic cancer.

BACKGROUND: Chemotherapy enhances survival rates for pancreatic cancer (PC) patients postsurgery, ye...

TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets.

Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-...

Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences.

Segmentation of infarcts is clinically important in ischemic stroke management and prognostication. ...

Accurate Identification of Cancer Cells in Complex Pre-Clinical Models Using a Deep-Learning Neural Network: A Transfection-Free Approach.

3D co-cultures are key tools for in vitro biomedical research as they recapitulate more closely the ...

Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.

Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) ...

scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data.

The recent advances in high-throughput single-cell sequencing have created an urgent demand for comp...

Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.

Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged ...

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant...

SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation.

Heart failure (HF) is a significant global public health concern with a high readmission rate, posin...

An attention-based deep learning for acute lymphoblastic leukemia classification.

The bone marrow overproduces immature cells in the malignancy known as Acute Lymphoblastic Leukemia ...

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