Oncology/Hematology

Other Cancers

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

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Hybrid model integration with explainable AI for brain tumor diagnosis: a unified approach to MRI analysis and prediction.

Effective treatment for brain tumors relies on accurate detection because this is a crucial health c...

A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images.

Cervical cancer is a major cause of mortality among women, particularly in low-income countries with...

Comparison of AI chatbot predicted and realworld survival outcomes in hepatocellular carcinoma.

This study compares survival predictions made by an artificial intelligence (AI) based chatbot with ...

Radiomics analysis based on dynamic contrast-enhanced MRI for predicting early recurrence after hepatectomy in hepatocellular carcinoma patients.

This study aimed to develop a machine learning model based on Magnetic Resonance Imaging (MRI) radio...

Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification.

Brain tumors are a significant contributor to cancer-related deaths worldwide. Accurate and prompt d...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized ...

A superpixel based self-attention network for uterine fibroid segmentation in high intensity focused ultrasound guidance images.

Ultrasound guidance images are widely used for high intensity focused ultrasound (HIFU) therapy; how...

Synergizing advanced algorithm of explainable artificial intelligence with hybrid model for enhanced brain tumor detection in healthcare.

Brain tumor causes life-threatening consequences due to which its timely detection and accurate clas...

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 d...

Deep learning-driven drug response prediction and mechanistic insights in cancer genomics.

In the field of cancer therapy, the diversity and heterogeneity of cancer genomes in clinical patien...

An enhanced deep learning model for accurate classification of ovarian cancer from histopathological images.

Ovarian Cancer is a malignancy that develops from ovarian cells and is frequently characterized by a...

Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.

This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in he...

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...

Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.

Classifying chondroid tumors is an essential step for effective treatment planning. Recently, with t...

A novel approach to overcome black box of AI for optical diagnosis in colonoscopy.

Accurate real-time optical diagnosis that distinguishes neoplastic from non-neoplastic colorectal le...

Deep learning model for grading carcinoma with Gini-based feature selection and linear production-inspired feature fusion.

The most common types of kidneys and liver cancer are renal cell carcinoma (RCC) and hepatic cell ca...

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 ...

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