Oncology/Hematology

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

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Showing 1009-1029 of 15,250 articles
Multiple Instance Learning for the Detection of Lymph Node and Omental Metastases in Carcinoma of the Ovaries, Fallopian Tubes and Peritoneum.

: Surgical pathology of tubo-ovarian and peritoneal cancer carries a well-recognised diagnostic work...

[Current status and trends of perioperative immunotherapy for gastric cancer].

In recent years,immunotherapy,particularly immune checkpoint inhibitors,has been widely used in the ...

[Progress of individualized precision therapy for peritoneal metastasis in gastric cancer].

Peritoneal metastasis represents the most aggressive form of gastric cancer metastasis and serves as...

Artificial intelligence in breast pathology: Overview and recent updates.

Breast cancer remains a major global health concern where timely and accurate pathologic diagnosis i...

Interpretable Machine Learning Models for Differentiating Glioblastoma From Solitary Brain Metastasis Using Radiomics.

PURPOSE: To develop and validate interpretable machine learning models for differentiating glioblast...

Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep Learning with Feature Fusion and Attention Mechanism.

RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for e...

Optimizing workflows for metastatic central nervous system disease: a systematic review and proposed guidelines.

INTRODUCTION: Brain and spine metastases are a major cause of morbidity and mortality in patients wi...

Deep Learning Auto-segmentation of Diffuse Midline Glioma on Multimodal Magnetic Resonance Images.

Diffuse midline glioma (DMG) H3 K27M-altered is a rare pediatric brainstem cancer with poor prognosi...

Radiomics applications in the modern management of esophageal squamous cell carcinoma.

Esophageal cancer ranks among the most lethal malignancies globally, with China accounting for more ...

Interpretable niche-based cell‒cell communication inference using multi-view graph neural networks.

Cell‒cell communication (CCC) is a fundamental biological process for the harmonious functioning of ...

Advancing breast, lung and prostate cancer research with federated learning. A systematic review.

Federated learning (FL) is advancing cancer research by enabling privacy-preserving collaborative tr...

PathoGraph: A Graph-Based Method for Standardized Representation of Pathology Knowledge.

Pathology data, primarily consisting of slides and diagnostic reports, inherently contain knowledge ...

China Protocol for early screening, precise diagnosis, and individualized treatment of lung cancer.

Early screening, diagnosis, and treatment of lung cancer are pivotal in clinical practice since the ...

Diversity of U1 Small Nuclear RNAs and Diagnostic Methods for Their Mutations.

U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various maligna...

Vessel-Like Microtunnels with Biomimetic Octopus Tentacles for Seizing and Detecting Exosomes to Diagnose Pancreatic Cancer.

Microchip-based exosome analysis has emerged as a promising approach for liquid biopsy in cancer dia...

Future Perspectives of Liver Research in the Asia-Pacific Region: Focus on Hepatitis B and C.

The Asia-Pacific region faces serious liver health challenges, primarily because of the comparativel...

A Clinically Annotated Transcriptomic Atlas of Nervous System Tumors.

BACKGROUND: While DNA methylation signatures are distinct across nervous system neoplasms, it has no...

A hybrid explainable federated-based vision transformer framework for breast cancer prediction via risk factors.

Breast cancer remains a leading cause of mortality in women, underscoring the need for timely and ac...

Generating dermatopathology reports from gigapixel whole slide images with HistoGPT.

Histopathology is the reference standard for diagnosing the presence and nature of many diseases, in...

Subregion-based radiomics analysis for predicting the histological grade of clear cell renal cell carcinoma.

PURPOSE: We explored the feasibility of constructing machine learning (ML) models based on subregion...

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