Oncology/Hematology

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

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Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.

BACKGROUND: Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) add...

Integrated multi-omics and machine learning reveal a gefitinib resistance signature for prognosis and treatment response in lung adenocarcinoma.

Gefitinib resistance (GR) presents a significant challenge in treating lung adenocarcinoma (LUAD), h...

Prediction model for ocular metastasis of breast cancer: machine learning model development and interpretation study.

BACKGROUND: Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cell...

Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning.

Integrating diverse types of biological data is essential for a holistic understanding of cancer bio...

Classification of melanoma skin Cancer based on Image Data Set using different neural networks.

This paper aims to address the pressing issue of melanoma classification by leveraging advanced neur...

Machine learning based on alcohol drinking-gut microbiota-liver axis in predicting the occurrence of early-stage hepatocellular carcinoma.

BACKGROUND: Alcohol drinking and gut microbiota are related to hepatocellular carcinoma (HCC), but t...

Development and validation of an individualized nomogram for predicting distant metastases in gastric cancer using a CT radiomics-clinical model.

PURPOSE: This study aimed to develop and validate a model for accurately assessing the risk of dista...

Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.

The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the ex...

The role of artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis.

Immune checkpoint inhibitors (ICIs) are revolutionizing cancer treatment, and Artificial Intelligenc...

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques.

Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable...

A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.

Identifying new compounds with minimal side effects to enhance patients' quality of life is the ulti...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cance...

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

BACKGROUND: Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and...

Artificial intelligence measured 3D lumbosacral body composition and clinical outcomes in rectal cancer patients.

INTRODUCTION: Patient body composition (BC) has been shown to help predict clinical outcomes in rect...

Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Early detection and precise characterization of brain tumors play a crucial role in improving patien...

F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study.

BACKGROUND: This study aims to develop habitat radiomic models to predict overall survival (OS) for ...

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