Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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A computational study of cardiac glycosides from Vernonia amygdalina as PI3K inhibitors for targeting HER2 positive breast cancer.

The PI3K/Akt pathway plays a crucial role in regulating a broad network of proteins involved in the ...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate ...

Machine learning models for predicting chemotherapy-induced adverse drug reactions in colorectal cancer patients.

BACKGROUND: Chemotherapy-induced adverse drug reactions (ADRs) are common in patients with colorecta...

Robot-Assisted Retrograde Intrarenal Surgery: A Mini Review of the Literature on Robotic Surgery Platforms for Endoscopic Stone Surgery.

Retrograde intrarenal surgery (RIRS) has become a cornerstone in renal stone management, with roboti...

Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis.

This study developed an immune-related long non-coding RNAs (lncRNAs)-based prognostic signature by ...

Impact of Normal Lung Volume Choices on Radiation Pneumonitis Risk Prediction in Locally Non-small Cell Lung Cancer Radiation Therapy.

PURPOSE: This study aims to evaluate the impact of varying definitions of normal lung volume on the ...

Precise metabolic dependencies of cancer through deep learning and validations.

Cancer cells exhibit metabolic reprogramming to sustain proliferation, creating metabolic vulnerabil...

Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy.

In nanostructure extraction, advanced techniques like synchrotron radiation and electron microscopy ...

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.

Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concer...

Intelligent assistant in radiation protection based on large language model with knowledge base.

Radiation protection is a critical pillar supporting the use of nuclear energy and nuclear technolog...

Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery.

BACKGROUND: Despite the widespread use of stereotactic radiosurgery (SRS) to treat cerebral arteriov...

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques.

Breast cancer remains a major cause of mortality among women, where early and accurate detection is ...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans,...

Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer.

Reconstructive flap surgery aims to restore the substance and function losses associated with tumor ...

Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant thre...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We ...

Predicting cisplatin response in cholangiocarcinoma patients using chromosome pattern and related gene expression.

Cholangiocarcinoma (CCA) is a prevalent bile duct cancer with limited treatment options. Cisplatin-b...

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