Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: Pediatric lymphoma patients undergo multiple 18F-FDG PET/CT examinations for staging and...
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the highly lethal and aggressive mal...
BACKGROUND: Growing evidence indicates that Folate Hydrolase 1 (FOLH1, also known as prostate-specif...
Gallbladder carcinoma, among the most prevalent malignancies of the biliary system, often presents w...
RATIONALE AND OBJECTIVES: In clinical practice, the preoperative risk assessment of adrenal metastas...
Artificial intelligence prognostic tools are now embedded in routine oncology workflows, generating ...
Hepatocellular carcinoma (HCC) frequently coexists with portal hypertension, significantly increasin...
The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates...
PURPOSE: magnetic resonance imaging (MRI)-based radiomics has emerged as a promising approach for no...
Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in earl...
The "Diabetic Retinal Disease (DRD) Cure Accelerator," a joint initiative by the Mary Tyler Moore Vi...
Cancer remains a major public health challenge driven by complex interactions among sociodemographic...
Mantle cell lymphoma (MCL) has a heterogeneous clinical course, making robust, usable prognostic too...
Hepatocellular carcinoma (HCC) is steadily increasing in incidence worldwide and requires data-drive...
Cancer registry data is an important resource in cancer research, e.g. to formulate hypotheses for n...
A range of underlying mechanistic relationships influences the incidence of cancer. Understanding th...
Liver cancer is a leading cause of cancer mortality; hepatocellular carcinoma (HCC), its predominant...
Cervical cancer (CC) causes significant mortality due to late diagnosis and limited understanding of...
The ABL1 gene encodes a non-receptor tyrosine kinase implicated in leukemia and other genetic disord...
We developed a machine learning model and validated it using a large-scale, real-world cohort to pre...
The growing capabilities of Large Language Models (LLMs) in understanding and generating clinical te...