Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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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...

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...

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...

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...

Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning.

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Tradition...

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...

Artificial intelligence in bone metastasis analysis: Current advancements, opportunities and challenges.

BACKGROUND: Artificial Intelligence is transforming medical imaging, particularly in the analysis of...

Radiomics and deep learning characterisation of liver malignancies in CT images - A systematic review.

BACKGROUND: Computed tomography (CT) has been widely used as an effective tool for liver imaging due...

Acquired resistance in cancer: towards targeted therapeutic strategies.

Development of acquired therapeutic resistance limits the efficacy of cancer treatments and accounts...

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...

Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection.

Electrical impedance spectroscopy (EIS) is a powerful tool used to investigate the properties of mat...

From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.

Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies....

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...

Targeting INF2 with DiosMetin 7-O-β-D-Glucuronide: a new stratagem for colorectal cancer therapy.

BACKGROUND AND PURPOSE: Colorectal cancer (CRC) is the third most prevalent malignancy in the gastro...

Prediction of pathological grade of oral squamous cell carcinoma and construction of prognostic model based on deep learning algorithm.

The aim of this study is to establish a deep learning model for predicting the pathological grade of...

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