Hematology

Leukemia

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

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Building a challenging medical dataset for comparative evaluation of classifier capabilities.

Since the 2000s, digitalization has been a crucial transformation in our lives. Nevertheless, digita...

Exploring spatiotemporal patterns of algal cell density in lake Dianchi with explainable machine learning.

The escalating global occurrence of algal blooms poses a growing threat to ecosystem services. In th...

Small sized centroblasts as poor prognostic factor in follicular lymphoma - Based on artificial intelligence analysis.

Histological assessment of centroblasts is an important evaluation in the diagnosis of follicular ly...

NNICE: a deep quantile neural network algorithm for expression deconvolution.

The composition of cell-type is a key indicator of health. Advancements in bulk gene expression data...

Performance Evaluation of a Novel Artificial Intelligence-Assisted Digital Microscopy System for the Routine Analysis of Bone Marrow Aspirates.

Bone marrow aspiration (BMA) smear analysis is essential for diagnosis, treatment, and monitoring of...

Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and...

Assessing screw length impact on bone strain in proximal humerus fracture fixation via surrogate modelling.

A high failure rate is associated with fracture plates in proximal humerus fractures. The causes of ...

Emergence of artificial intelligence for automating cone-beam computed tomography-derived maxillary sinus imaging tasks. A systematic review.

Cone-beam computed tomography (CBCT) imaging of the maxillary sinus is indispensable for implantolog...

Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.

Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for...

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell ...

Time-Series MR Images Identifying Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using a Deep Learning Approach.

BACKGROUND: Pathological complete response (pCR) is an essential criterion for adjusting follow-up t...

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell developmen...

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma.

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential...

Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease.

Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is a principal ...

Machine learning-based model for predicting outcomes in cerebral hemorrhage patients with leukemia.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with h...

Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.

The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of ...

Machine Learning-Enhanced Quantum Chemistry-Assisted Refinement of the Active Site Structure of Metalloproteins.

Understanding the fine structural details of inhibitor binding at the active site of metalloenzymes ...

An artificial intelligence-assisted clinical framework to facilitate diagnostics and translational discovery in hematologic neoplasia.

BACKGROUND: The increasing volume and intricacy of sequencing data, along with other clinical and di...

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