Oncology/Hematology

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

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Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers.

One of the foremost causes of global healthcare burden is cancer of the gastrointestinal tract. The ...

Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment.

Liver cancer remains one of the most formidable challenges in modern medicine, characterized by its ...

Indole 3-acetate and response to therapy in borderline resectable or locally advanced pancreatic cancer.

BACKGROUND/AIMS: It was recently reported that a higher concentration of the bacterially produced me...

An in-depth examination of the fuzzy fractional cancer tumor model and its numerical solution by implicit finite difference method.

The cancer tumor model serves a s a crucial instrument for understanding the behavior of different c...

Improving prediction of solar radiation using Cheetah Optimizer and Random Forest.

In the contemporary context of a burgeoning energy crisis, the accurate and dependable prediction of...

Machine learning-based integration develops a disulfidptosis-related lncRNA signature for improving outcomes in gastric cancer.

Gastric cancer remains one of the deadliest cancers globally due to delayed detection and limited tr...

Artificial Intelligence-Empowered Multistep Integrated Radiation Therapy Workflow for Nasopharyngeal Carcinoma.

PURPOSE: To establish an artificial intelligence (AI)-empowered multistep integrated (MSI) radiation...

Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.

BACKGROUND: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiothera...

Deep learning-based intratumoral and peritumoral features for differentiating ocular adnexal lymphoma and idiopathic orbital inflammation.

OBJECTIVES: To evaluate the value of deep-learning-based intratumoral and peritumoral features for d...

Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prev...

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Medical image analysis has significantly benefited from advancements in deep learning, particularly ...

Development of two machine learning models to predict conversion from primary HER2-0 breast cancer to HER2-low metastases: a proof-of-concept study.

BACKGROUND: HER2-low expression has gained clinical relevance in breast cancer (BC) due to the avail...

Transferable deep learning with coati optimization algorithm based mitotic nuclei segmentation and classification model.

Image processing and pattern recognition methods have recently been extensively implemented in histo...

Geometric deep learning improves generalizability of MHC-bound peptide predictions.

The interaction between peptides and major histocompatibility complex (MHC) molecules is pivotal in ...

A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides.

Mitotic activity is an important feature for grading several cancer types. However, counting mitotic...

Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning.

BACKGROUND: The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting fo...

High density of TCF1+ stem-like tumor-infiltrating lymphocytes is associated with favorable disease-specific survival in NSCLC.

INTRODUCTION: Tumor-infiltrating lymphocytes are both prognostic and predictive biomarkers for immun...

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