Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: The use of endovascular procedures is becoming increasingly popular across multiple clin...
Accurately predicting druggable genes is of paramount importance for enhancing the efficacy of targe...
BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, gi...
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations ...
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI fea...
Lymph node metastasis in intrahepatic cholangiocarcinoma significantly impacts overall survival, emp...
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long duration...
BACKGROUND AND OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) is recommended a...
BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, of...
Colorectal cancer (CRC) is one of the deadliest malignancies globally, with high incidence and morta...
In breast cancer treatment, accurately predicting how long a patient will survive is crucial for dec...
Using Raman spectroscopy (RS) signals for skin cancer tissue classification has recently drawn signi...
By modeling the temporal dependencies of sleep sequence, advanced automatic sleep staging algorithms...
Sleep staging is essential for sleep assessment and plays an important role in disease diagnosis, wh...
Pathological examination of nasopharyngeal carcinoma (NPC) is an indispensable factor for diagnosis,...
INTRODUCTION: Cancer-associated fibroblasts (CAFs) are a diverse group of cells that significantly c...
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. T...
RATIONALE AND OBJECTIVES: To develop interpretable machine learning models that utilize deep learnin...
BackgroundBreast cancer results from an uncontrolled growth of breast tissue. Many methods of diagno...
Machine learning models for the diagnosis of breast cancer can facilitate the prediction of cancer r...
The pharmaceutical industry has increasingly adopted model-informed drug discovery and development (...