Latest AI and machine learning research in brain cancer for healthcare professionals.
To investigate the impact of combining the high-resolution (Hi-res) scan mode with deep learning ima...
Many cancer patients die due to their treatment failing because of their disease's resistance to che...
The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted,...
BACKGROUND: Lung cancer has the highest mortality rate among cancers. Radiation therapy (RT) is one ...
BACKGROUND: In view of the underlying health risks posed by X-ray radiation, the main goal of the pr...
The prevalence and pervasiveness of artificial intelligence (AI) with medical images in veterinary a...
Instantaneous photosynthetically available radiation (IPAR) at the ocean surface and its vertical pr...
Many technological advances have entered the clinical routine of Computed Tomography (CT) imaging. T...
Automatic image registration plays an important role in many aspects of the radiation oncology workf...
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT) and thei...
Radiation oncology is a field that heavily relies on new technology. Data science and artificial int...
Ensemble learning is a kind of machine learning method which can integrate multiple basic learners t...
Due to the potential difference between two neurons and that between the inner and outer membranes o...
Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue typ...
We describe two cases of locally advanced rectal cancer (LARC) treated with robot-assisted total pel...
BACKGROUND: Diagnostic classification of diffuse gliomas now requires an assessment of molecular fea...
An increasing number of cancer patients are of advanced age as the incidence of cancer increases wit...
Cancer therapeutics cause various treatment-related changes that may impact patient follow-up and di...
Intelligent and precision medical treatment is the future development trend of surgical operations. ...
MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs...
AIM: To describe a deep convolutional generative adversarial networks (DCGAN) model which learns nor...