Oncology/Hematology

Other Cancers

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

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Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.

The choice of imaging modalities is essential in sarcoma management, as different techniques provide...

Foundation Model and Radiomics-Based Quantitative Characterization of Perirenal Fat in Renal Cell Carcinoma Surgery.

RATIONALE AND OBJECTIVES: To quantitatively characterize the degree of perirenal fat adhesion using ...

A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.

INTRODUCTION: Tumor-infiltrating B lymphocytes (TILBs) play a pivotal role in shaping the immune mic...

Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction.

Preoperative classification of brain tumors is critical to developing personalized treatment plans, ...

Artificial intelligence-assisted magnetic resonance lymphography for evaluation of micro- and macro-sentinel lymph node metastasis in breast cancer.

Contrast-enhanced magnetic resonance lymphography (CE-MRL) plays a crucial role in preoperative diag...

Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis.

The task of predicting liver tumors is critical as part of medical image analysis and genomics area ...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamo...

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation.

Multimodality is often necessary for improving object segmentation tasks, especially in the case of ...

Brain tumor segmentation with deep learning: Current approaches and future perspectives.

BACKGROUND: Accurate brain tumor segmentation from MRI images is critical in the medical industry, d...

Machine Learning and Mendelian Randomization Reveal a Tumor Immune Cell Profile for Predicting Bladder Cancer Risk and Immunotherapy Outcomes.

This study's objective was to develop predictive models for bladder cancer (BLCA) using tumor infilt...

HistoMSC: Density and topology analysis for AI-based visual annotation of histopathology whole slide images.

We introduce an end-to-end framework for the automated visual annotation of histopathology whole sli...

Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion.

Malignant pleural effusion (MPE) is a common complication in patients with advanced lung cancer, sig...

A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer.

Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with canc...

Artificial intelligence to enhance the diagnosis of ocular surface squamous neoplasia.

To provide an artificial intelligence (AI) method using in vivo confocal microscopy (IVCM) to differ...

Integrated AI and machine learning pipeline identifies novel WEE1 kinase inhibitors for targeted cancer therapy.

The dysregulation of the cell cycle in cancer underscores the therapeutic potential of targeting WEE...

Artificial Intelligence and Convolutional Neural Networks-Driven Detection of Micro and Macro Metastasis of Cutaneous Melanoma to the Lymph Nodes.

BACKGROUND: Lymph node (LN) assessment is a critical component in the staging and management of cuta...

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