Oncology/Hematology

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

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A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images.

OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining ...

Few-Shot Learning for Prostate Cancer Detection on MRI: Comparative Analysis with Radiologists' Performance.

Deep-learning models for prostate cancer detection typically require large datasets, limiting clinic...

Artificial Intelligence-Powered Spatial Analysis of Immune Phenotypes in Resected Pancreatic Cancer.

IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) have been implicated as prognostic biomar...

Mapping breast cancer research on monoclonal antibodies: a data-driven approach using VOSviewer, Bibliometrix, and CiteSpace.

Monoclonal Antibodies and Breast Cancer Research (MABCR) has progressed substantially, particularly ...

High-performance Open-source AI for Breast Cancer Detection and Localization in MRI.

Purpose To develop and evaluate an open-source deep learning model for detection and localization o...

Exploring the complex interplay between oral infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs.

() is an oral commensal bacterium that can become pathogenic and is associated with periodontitis, ...

Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.

UNLABELLED: Growing research evidence indicates a substantial influence of the intra-tumor microbiom...

Deep learning algorithms from histopathological images stratify molecular subtypes for leiomyosarcoma: a proof-and-concept diagnostic study.

BACKGROUND: The leiomyosarocma (LMS) is the most common soft tissue sarcoma, and its molecular subty...

Machine learning-driven national analysis for predicting adverse outcomes in intramedullary spinal cord tumor surgery.

UNLABELLED: Spinal tumors represent 15% of all central nervous system malignancies, with intramedull...

Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.

Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-bei...

Mini-review: Perioperative pain management in gynecologic oncology - strategies and future directions.

This mini-review discusses important factors in opioid use in gynecologic oncology in the perioperat...

Differentiating adenocarcinoma and squamous cell carcinoma in lung cancer using semi automated segmentation and radiomics.

INTRODUCTION: Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are frequently observed forms of...

Diagnostic Study of Head and Neck Metastatic Tumors From Different Primary Sites Based on Stacking Machine Learning Methods.

Metastatic tumors of the head and neck (MTHN) typically indicate advanced disease with a poor progno...

AI-based large-scale screening of gastric cancer from noncontrast CT imaging.

Early detection through screening is critical for reducing gastric cancer (GC) mortality. However, i...

Preoperative Assessment of Lymph Node Metastasis in Rectal Cancer Using Deep Learning: Investigating the Utility of Various MRI Sequences.

PURPOSE: This study aimed to develop a deep learning (DL) model based on three-dimensional multi-par...

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