Hematology

Lymphoma

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

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Deep Learning and Hyperspectral Imaging for Liver Cancer Staging and Cirrhosis Differentiation.

Liver malignancies, particularly hepatocellular carcinoma (HCC), pose a formidable global health cha...

Artificial neural networks' estimations of lower-limb kinetics in sidestepping: Comparison of full-body vs. lower-body landmark sets.

Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This st...

Deep Learning Predicts Non-Normal Transmission Distributions in High-Field Asymmetric Waveform Ion Mobility (FAIMS) Directly from Peptide Sequence.

Peptide ion mobility adds an extra dimension of separation to mass spectrometry-based proteomics. Th...

Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.

Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise fr...

Machine-learning model based on ultrasomics for non-invasive evaluation of fibrosis in IgA nephropathy.

OBJECTIVES: To develop and validate an ultrasomics-based machine-learning (ML) model for non-invasiv...

Detecting B-cell lymphoma-6 overexpression status in primary central nervous system lymphoma using multiparametric MRI-based machine learning.

PURPOSE: In primary central nervous system lymphoma (PCNSL), B-cell lymphoma-6 (BCL-6) is an unfavor...

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection ...

ChatGPT 4.0's efficacy in the self-diagnosis of non-traumatic hand conditions.

BACKGROUND: With advancements in artificial intelligence, patients increasingly turn to generative A...

KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics.

KanCell is a deep learning model based on Kolmogorov-Arnold networks (KAN) designed to enhance cellu...

Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation.

BACKGROUND: The application of natural language processing in medicine has increased significantly, ...

The 'Sandwich' meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding.

. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Elec...

Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors.

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning ...

Death risk prediction model for patients with non-traumatic intracerebral hemorrhage.

BACKGROUND: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage...

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