Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment.

Head and neck squamous cell carcinoma (HNSCC) remains a globally prevalent malignancy with high morb...

Multimodal Artificial Intelligence Using Endoscopic USG, CT, and MRI to Differentiate Between Serous and Mucinous Cystic Neoplasms.

Introduction Serous cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) often exhibit similar...

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 ...

Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.

Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing signifi...

Insight into microbial extracellular vesicles as key communication materials and their clinical implications for lung cancer (Review).

The complexity of lung cancer, driven by multifactorial causes such as genetic, environmental and li...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendo...

Neurodegeneration Promotes Tumorigenesis in Colorectal Cancer: Insights From Single-Cell and Spatial Multiomics.

PURPOSE: Colorectal cancer (CRC) ranks third in global incidence and second in mortality, with rates...

Long-term exposure to PM and liver cancer mortality: Insights into the role of smaller particulate fractions.

Particulate matter (PM) is a recognized carcinogen, but the effects of PM on liver cancer remain und...

MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing sp...

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the pr...

A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation.

In clinical medicine, a reliable and resource-friendly computer-aided diagnosis (CAD) method for bra...

Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning.

The pancreas is a gland in the abdomen that helps to produce hormones and digest food. The irregular...

GNNs surpass transformers in tumor medical image segmentation.

To assess the suitability of Transformer-based architectures for medical image segmentation and inve...

Machine learning framework coupled with CADD for predicting sphingosine kinase 1 inhibitors.

Sphingosine kinase 1 (SphK1) plays a pivotal role in cancer progression, metastasis, and chemotherap...

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