Latest AI and machine learning research in cardiovascular for healthcare professionals.
To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined wit...
This study aimed to compare the long-term outcomes of breast-conserving surgery plus radiotherapy (B...
BACKGROUND AND PURPOSE: During the ESTRO 2023 physics workshop on "AI for the fully automated radiot...
RATIONALE AND OBJECTIVES: This study evaluated the performance of super-resolution deep learning-bas...
RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate dia...
BACKGROUND: Long-lasting efforts have been made to reduce radiation dose and thus the potential radi...
Supercritical fluids (SCFs) can be used to prepare drugs nanoparticles with improved solubility. SCF...
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evalu...
An early detection of lung tumors is critical for better treatment results, and CT scans can reveal ...
BACKGROUND: Radiation dose should be as low as reasonably achievable. With the invention of photon-c...
Cancer stem cells (CSCs) have the potential to self-renew and induce cancer, which may contribute to...
We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiom...
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation f...
In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality...
Boron neutron capture therapy (BNCT) is a highly targeted, selective and effective technique to cure...
Acute radiation dermatitis (ARD) is a common and distressing issue for cancer patients undergoing ra...
Early detection and treatment of breast cancer can significantly reduce patient mortality, and mammo...
Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristic...
RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before tre...
The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-a...
RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics ...