Oncology/Hematology

Other Cancers

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

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[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...

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 ...

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

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

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...

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...

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...

AI-based multimodal prediction of lymph node metastasis and capsular invasion in cT1N0M0 papillary thyroid carcinoma.

BACKGROUND: Accurate preoperative evaluation of cT1N0M0 papillary thyroid carcinoma (PTC) is essenti...

Multilevel Inter-modal and Intra-modal Transformer network with domain adversarial learning for multimodal sleep staging.

Sleep staging identification is a fundamental task for the diagnosis of sleep disorders. With the de...

Improving brain tumor diagnosis: A self-calibrated 1D residual network with random forest integration.

Medical specialists need to perform precise MRI analysis for accurate diagnosis of brain tumors. Cur...

Machine learning-driven prognostic model based on sphingolipid-related gene signature in pancreatic cancer: development and validation.

BACKGROUND: Pancreatic cancer, a highly malignant tumor with poor prognosis, lacks effective early d...

Radiomics-Based Classification of Clear Cell Renal Cell Carcinoma ISUP Grade: A Machine Learning Approach with SHAP-Enhanced Explainability.

: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer, and its progno...

Radiomics based on dual-energy CT for noninvasive prediction of cervical lymph node metastases in patients with nasopharyngeal carcinoma.

INTRODUCTION: To develop and validate a machine learning model based on dual-energy computed tomogra...

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks.

Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequenc...

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