Oncology/Hematology

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

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FFLUNet: Feature Fused Lightweight UNet for brain tumor segmentation.

Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types...

Metastatic hepatic carcinoma: Mechanisms, emerging therapeutics, and future perspectives.

Metastatic hepatic carcinoma (MHC) remains a lethal disease, with a 5-year survival rate of around 1...

Stereotactic Body Radiation Therapy for Primary Renal Cancer and Genetic Markers of Response: A Phase 2 Trial.

Controlled outcome assessment of radiotherapy for primary renal cell carcinoma (RCC) remains limited...

'Bill': An artificial intelligence (AI) clinical scenario coach for medical radiation science education.

INTRODUCTION: The integration of artificial intelligence (AI) into medical radiation science (MRS) e...

Optimizing malignancy prediction: A comparative analysis of transfer learning techniques on EBUS images.

BACKGROUND: Improving diagnostic accuracy in EBUS image analysis using machine learning is a current...

Qualitative evaluation of automatic liver segmentation in computed tomography images for clinical use in radiation therapy.

PURPOSE: Segmentation of target volumes and organs at risk on computed tomography (CT) images consti...

Artificial Intelligence in cancer epigenomics: a review on advances in pan-cancer detection and precision medicine.

DNA methylation is a fundamental epigenetic modification that regulates gene expression and maintain...

A multimodal fusion system predicting survival benefits of immune checkpoint inhibitors in unresectable hepatocellular carcinoma.

Early identification of unresectable hepatocellular carcinoma (HCC) patients who may benefit from im...

Comparative analysis of pre-transcatheter aortic valve implantation CTA protocols: Optimizing radiation dose and contrast volume.

BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TA...

Comprehensive statistical and machine learning framework for identification of metabolomic biomarkers in breast cancer.

INTRODUCTION: Breast cancer is the most common cancer among women, with its burden increasing over t...

Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis.

BACKGROUND: Chordomas are primary bone lesions originating from embryonic notochord remnants, most c...

Multi-class transformer-based segmentation of pancreatic ductal adenocarcinoma and surrounding structures in CT imaging: a multi-center evaluation.

OBJECTIVE: Accurate segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding anatomic...

Predictive Modelling Using Thyroid Cartilage Segmentation and Radiomic Features: A Feasibility Study.

UNLABELLED: Laryngeal cancer, one of the top three head and neck cancers, requires timely diagnosis ...

A tumor microenvironment model for glioma diagnosis and therapeutic evaluation based on the analysis of tissues and biological fluids.

Traditional glioma diagnostic methods have limitations, while liquid biopsy is a promising non-invas...

The Diagnostic Value of Artificial Intelligence in Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI) in detecting oral ...

Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer.

The liver exhibits extensive circadian regulation among organs. Epidemiological studies have substan...

Establishing predictive machine learning models for drug responses in patient derived cell culture.

The concept of personalised medicine in cancer therapy is becoming increasingly important. There alr...

Deep learning-based quantification of eosinophils and lymphocytes shows complementary prognostic effects in colorectal cancer patients.

The immune microenvironment of colorectal cancer is a major component of the disease and influences ...

Unraveling the interrelationship between breast cancer and endometriosis based on multi-omics analysis.

BACKGROUND: Endometriosis and breast cancer are significant global health burdens affecting women wo...

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