Oncology/Hematology

Other Cancers

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

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CTSS in the tumor microenvironment links immune escape and immunotherapy sensitivity in kidney renal clear cell carcinoma.

The tumor microenvironment (TME) of kidney renal clear cell carcinoma (KIRC) exhibits complex dynami...

A web-based prediction model for brain metastasis in non-small cell lung cancer patients.

BACKGROUND: Brain metastasis (BM) stands as a significant contributor to mortality among cancer pati...

Physics-informed machine learning digital twin for reconstructing prostate cancer tumor growth via PSA tests.

Existing prostate cancer monitoring methods, reliant on prostate-specific antigen (PSA) measurements...

Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.

The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessmen...

Noninvasive and Sensitive Biosensor for the Detection of Oral Cancer Prognostic Biomarkers.

Early detection of oral squamous cell carcinoma (OSCC) significantly enhances treatment outcomes and...

Radiomics meets transformers: A novel approach to tumor segmentation and classification in mammography for breast cancer.

ObjectiveThis study aimed to develop a robust framework for breast cancer diagnosis by integrating a...

Radiomics with Machine Learning Improves the Prediction of Microscopic Peritumoral Small Cancer Foci and Early Recurrence in Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning model using ...

Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer ...

A bibliometric analysis reveals a dynamic growth in the use of artificial intelligence in oral cancer research over three decades.

Oral cancer (OC) remains a significant malignant neoplasm in both the developed and developing world...

A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude.

Deep learning techniques have become pivotal in medical image segmentation, but their success often ...

Gut microbiota and SCFAs improve the treatment efficacy of chemotherapy and immunotherapy in NSCLC.

The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on t...

Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection.

Breast cancer is a relatively common carcinoma among women worldwide and remains a considerable publ...

Detecting and classifying the mechanics of cancer and non-cancer cells by machine learning algorithm.

The global burden of cancer has increased in recent years, posing a major public health challenge. G...

Artificial intelligence-driven pathomics in hepatocellular carcinoma: current developments, challenges and perspectives.

Hepatocellular carcinoma (HCC) is a highly malignant tumor with elevated incidence and mortality rat...

Advancements in lung cancer: molecular insights, innovative therapies, and future prospects.

Still among the most common and deadly cancers worldwide, lung cancer causes major morbidity and dea...

Performance Evaluation of Artificial Intelligence Techniques in the Diagnosis of Brain Tumors: A Systematic Review and Meta-Analysis.

Brain tumors are becoming more prevalent, often leading to severe disability and high mortality rate...

AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost.

Skin cancer is a significant global public health issue, with millions of new cases identified each ...

Predicting Mechanosensitive T Cell Expansion from Cell Spreading.

Variability in T cell performance presents a major challenge to adoptive cellular immunotherapy (ACT...

A visualized machine learning model using noninvasive parameters to differentiate men with and without prostatic carcinoma before biopsy.

This study aimed to create a visualized extreme gradient boosting (XGBOOST) model to distinguish pro...

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