Hematology

Lymphoma

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

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Automated Diffusion Analysis for Non-Invasive Prediction of IDH Genotype in WHO Grade 2-3 Gliomas.

BACKGROUND AND PURPOSE: Glioma molecular characterization is essential for risk stratification and t...

Automated classification of seizure onset pattern using intracranial electroencephalogram signal of non-human primates.

To develop and validate a machine learning framework for the classification of distinct seizure onse...

Identification of Isomerically Diverse Ginsenosides Using Engineered Aerolysin Nanopore via Non-Translocation Blockade Sensing.

Typical nanopore sensing depends on slowed translocation through the pore to acquire effective block...

Deep learning assisted non-invasive lymph node burden evaluation and CDK4/6i administration in luminal breast cancer.

Precise lymph node evaluation is fundamental to optimize CDK4/6 inhibitor therapy in luminal breast ...

Detecting genetic interactions with visible neural networks.

Non-linear interactions among single nucleotide polymorphisms (SNPs), genes, and pathways play an im...

Vascular segmentation of functional ultrasound images using deep learning.

Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and ...

Simulating Open Quantum Dynamics with a Neural Network-Enhanced Non-Markovian Stochastic Schrödinger Equation.

The non-Markovian stochastic Schrödinger equation (NMSSE) offers a promising approach for open quant...

UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.

PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcino...

The tumor microenvironment of non-small cell lung cancer impairs immune cell function in people with HIV.

Lung cancer is the leading cause of cancer mortality among people with HIV (PWH), with increased inc...

Visualizing fatigue mechanisms in non-communicable diseases: an integrative approach with multi-omics and machine learning.

BACKGROUND: Fatigue is a prevalent and debilitating symptom of non-communicable diseases (NCDs); how...

Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms.

In this study, the ability of machine learning algorithms to predict tensile properties of both heat...

Tumor-specific draining lymph node CD8 T cells orchestrate an anti-tumor response to neoadjuvant PD-1 immune checkpoint blockade.

Elucidating the anti-tumor role of tumor-draining lymph nodes (tdLNs) in patients could offer critic...

Performance of AI methods in PET-based imaging for outcome prediction in lymphoma: A systematic review and meta-analysis.

OBJECTIVES: To evaluate the predictive performance of artificial intelligence (AI) methods using pre...

Machine-learning-informed scattering correlation analysis of sheared colloids.

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to q...

Optimizing Attenuation Correction in Ga-PSMA PET Imaging Using Deep Learning and Artifact-Free Dataset Refinement.

Attenuation correction (AC) is essential for achieving quantitatively accurate PET imaging. In Ga-P...

Prediction of Lymph Node Metastasis in Non-Small Cell Lung Carcinoma Using Primary Tumor Somatic Mutation Data.

PURPOSE: Lymph node metastasis (LNM) significantly affects prognosis and treatment strategies in non...

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