Hematology

Lymphoma

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

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Raised Leptin and Pappalysin2 cell-free RNAs are the hallmarks of pregnancies complicated by preeclampsia with fetal growth restriction.

Preeclampsia (PE) and fetal growth restriction (FGR) complicate 5-10% of pregnancies and are major c...

Comparison of conventional and radiomics-based analysis of myocardial infarction using multimodal non-linear optical microscopy.

Myocardial infarction, a leading cause of mortality worldwide, leaves survivors at significant risk ...

Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery.

BACKGROUND: Unplanned postoperative intensive care unit admissions (UIAs) are rare events that cause...

Non-invasive tests of fibrosis in the management of MASLD: revolutionising diagnosis, progression and regression monitoring.

With the recent conditional approval of resmetirom by the US Food and Drug Administration, the treat...

Diagnostics of Autoimmune Hepatitis Enabled by Non-Invasive Clinical Proteomics.

BACKGROUND: Autoimmune hepatitis (AIH) may be difficult to diagnose and distinguish clinically and b...

In Silico tool for predicting, designing and scanning IL-2 inducing peptides.

Interleukin-2 (IL-2) based immunotherapy has been approved for treating certain types of cancer, as ...

A non-anatomical graph structure for boundary detection in continuous sign language.

Recently, the challenge of the boundary detection of isolated signs in a continuous sign video has b...

An interpretable machine learning model for predicting bone marrow invasion in patients with lymphoma via F-FDG PET/CT: a multicenter study.

PURPOSE: Accurate identification of bone marrow invasion (BMI) is critical for determining the progn...

Non-invasive liver fibrosis screening on CT images using radiomics.

PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of ...

Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.

Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet ac...

Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.

OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic f...

How large is the universe of RNA-like motifs? A clustering analysis of RNA graph motifs using topological descriptors.

Identifying novel and functional RNA structures remains a significant challenge in RNA motif design ...

Nanozyme-Enabled Multimodal Sensing: Visual and Rapid Profiling of Extracellular Vesicles.

CD20, a transmembrane protein on the surface of lymphoma extracellular vesicles (EVs), is highly exp...

A Novel Machine Learning Model for Predicting Natural Conception Using Non-Laboratory-Based Data.

This study aimed to predict the likelihood of natural conception among couples by using a machine le...

Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity.

Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope o...

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