Hematology

Lymphoma

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

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Automatic Detection of B-Lines in Lung Ultrasound Based on the Evaluation of Multiple Characteristic Parameters Using Raw RF Data.

B-line artifacts in lung ultrasound, pivotal for diagnosing pulmonary conditions, warrant automated ...

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately pred...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is ...

Non-traditional socio-environmental and geospatial determinants of Alzheimer's disease-related dementia mortality.

IMPORTANCE: Recent data point to the impact of non-traditional environmental and social factors on A...

Trustworthy AI for stage IV non-small cell lung cancer: Automatic segmentation and uncertainty quantification.

Accurate segmentation of lung tumors is essential for advancing personalized medicine in non-small c...

Evaluating crash risk factors of farm equipment vehicles on county and non-county roads using interpretable tabular deep learning (TabNet).

Crashes involving farm equipment vehicles are a significant safety concern on public roads, particul...

Semi-supervised non-negative matrix factorization with structure preserving for image clustering.

Semi-supervised learning methods have wide applications thanks to the reasonable utilization for a p...

LMP-GAN: Out-of-Distribution Detection for Non-Control Data Malware Attacks.

Anomaly detection is a common application of machine learning. Out-of-distribution (OOD) detection i...

StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation.

Federated learning is a distributed learning framework that takes full advantage of private data sam...

Approximation by non-symmetric networks for cross-domain learning.

For the past 30 years or so, machine learning has stimulated a great deal of research in the study o...

Machine learning-assisted Fourier transform infrared spectroscopy to predict adulteration in coriander powder.

Coriander is a widely used spice, valued for its flavor, aroma, and nutritional benefits in various ...

Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.

Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the ch...

The machine learning prediction model of non-alcoholic fatty liver; the role of hydrogen and methane breath tests.

Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of global chronic liver disease, a...

Development of Machine Learning-Based Models for Mutagenicity Predictions with Applications to Non-Sugar Sweeteners.

Artificial sweeteners, often known as non-sugar sweeteners (NSSs), have been utilized as food additi...

TIGPR: A multi-view ground penetrating radar detection data for damage assessment of transportation infrastructure.

The TIGPR dataset is a high-quality collection of ground-penetrating radar (GPR) images designed for...

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