Oncology/Hematology

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

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Showing 484-504 of 15,198 articles
Heterogeneity Habitats -Derived Radiomics of Gd-EOB-DTPA Enhanced MRI for Predicting Proliferation of Hepatocellular Carcinoma.

OBJECTIVE: To construct and validate the optimal model for preoperative prediction of proliferative ...

Sitting time and risk of cancer incidence and cancer mortality in postmenopausal women: the Women's Health Accelerometry Collaboration.

PURPOSE: Few studies have explored whether accelerometer-measured sedentary behavior increases cance...

Intelligent assistant in radiation protection based on large language model with knowledge base.

Radiation protection is a critical pillar supporting the use of nuclear energy and nuclear technolog...

Informatics at the Frontier of Cancer Research.

Digitized healthcare data, high-throughput profiling technologies, and data repositories have facili...

A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques.

In this paper, three Double Machine Learning (DML) models are proposed to enhance the accuracy of br...

Deep learning strategies for semantic segmentation of pediatric brain tumors in multiparametric MRI.

Automated segmentation of pediatric brain tumors (PBTs) can support precise diagnosis and treatment ...

Developing transferable and universal IR biomarkers for intraoperative colorectal cancer diagnosis via FTIR spectroscopy.

Histological staining has long been the gold standard for cancer detection, but it is limited by sub...

LncRNAs regulates cell death in osteosarcoma.

Despite improvements, prognosis in osteosarcoma patients remains poor, making it essential to identi...

Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation.

Lung adenocarcinoma (LUAD) is a major challenge in oncology due to its complex molecular structure a...

Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis.

Exosomes are crucial in the development of non-small cell lung cancer (NSCLC), yet exosome-associate...

Hierarchical in-out fusion for incomplete multimodal brain tumor segmentation.

Fusing multimodal data play a crucial role in accurate brain tumor segmentation network and clinical...

AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis.

Lung cancer remains the leading cause of cancer-related mortality worldwide, necessitating accurate ...

RareNet: a deep learning model for rare cancer diagnosis.

Although significant advances have been made in the early detection of many cancers, challenges rema...

Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.

PANoptosis is closely associated with tumorigenesis and therapeutic response, yet its role in multip...

Multi channel fusion diffusion models for brain tumor MRI data augmentation.

The early diagnosis of brain tumors is crucial for patient prognosis, and medical imaging techniques...

Cervical cancer prediction using machine learning models based on routine blood analysis.

Cervical cancer (CC) is the fourth most common cancer among women globally. The key to preventing an...

Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.

Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlight...

CLASEG: advanced multiclassification and segmentation for differential diagnosis of oral lesions using deep learning.

Oral cancer has a high mortality rate primarily due to delayed diagnoses, highlighting the need for ...

Clustering cell nuclei on microgrooves for disease diagnosis using deep learning.

Various diseases including laminopathies and certain types of cancer are associated with abnormal nu...

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