Oncology/Hematology

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

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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...

Using machine learning for predicting cancer-specific mortality in bladder cancer patients undergoing radical cystectomy: a SEER-based study.

BACKGROUND: Accurately assessing the prognosis of bladder cancer patients after radical cystectomy h...

A risk prediction model for gastric cancer based on endoscopic atrophy classification.

BACKGROUNDS: Gastric cancer (GC) is a prevalent malignancy affecting the digestive system. We aimed ...

Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.

Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The im...

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...

Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.

Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targ...

A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation.

Colorectal cancer (CRC) is a prevalent gastrointestinal tumor worldwide with high morbidity and mort...

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, ye...

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...

Large Language Models as Decision-Making Tools in Oncology: Comparing Artificial Intelligence Suggestions and Expert Recommendations.

PURPOSE: To determine the accuracy of large language models (LLMs) in generating appropriate treatme...

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...

American College of Veterinary Radiology and European College of Veterinary Diagnostic Imaging position statement on artificial intelligence.

The American College of Veterinary Radiology (ACVR) and the European College of Veterinary Diagnosti...

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...

Compressed Representation of Extreme Learning Machine with Self-Diffusion Graph Denoising Applied for Dissecting Molecular Heterogeneity.

Molecular heterogeneity exists in many biological systems, such as major malignancies or diverse cel...

Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers known to humans. However, ...

Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm.

With the advancement of medical technology, a large amount of complex data on cancers is produced fo...

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