Latest AI and machine learning research in brain cancer for healthcare professionals.
Many cancer patients die due to their treatment failing because of their disease's resistance to chemotherapy and other forms of radiation therapy. Resistance may develop at any stage of therapy, even at the beginning. Several factors influence current therapy, including the type of cancer and the existence of genetic abnormalities. The response to treatment is not always predicted by the existenc...
The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted, facilitating increased cancer detection and lower recall rates compared with those achieved by using full-field digital mammography (DM). However, the use of DBT, as compared with DM, raises new challenges, including a larger number of acquired images and thus longer interpretation times. While mos...
BACKGROUND: Lung cancer has the highest mortality rate among cancers. Radiation therapy (RT) is one of the most effective therapies for lung cancer. T...
BACKGROUND: In view of the underlying health risks posed by X-ray radiation, the main goal of the present research is to achieve high-quality CT image...
The prevalence and pervasiveness of artificial intelligence (AI) with medical images in veterinary and human medicine is rapidly increasing. This arti...
Instantaneous photosynthetically available radiation (IPAR) at the ocean surface and its vertical profile below the surface play a critical role in mo...
Many technological advances have entered the clinical routine of Computed Tomography (CT) imaging. The new CT scanners have specific solutions in gant...
Automatic image registration plays an important role in many aspects of the radiation oncology workflow ranging from treatment simulation, image guide...
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT) and their integration into modern software-based systems r...
Radiation oncology is a field that heavily relies on new technology. Data science and artificial intelligence will have an important role in the entir...
Ensemble learning is a kind of machine learning method which can integrate multiple basic learners together and achieve higher accuracy. Recently, sin...
BACKGROUND: Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain con...
Due to the potential difference between two neurons and that between the inner and outer membranes of an individual neuron, the neural network is alwa...
Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue types and prognosis. They could be graded with four l...
We describe two cases of locally advanced rectal cancer (LARC) treated with robot-assisted total pelvic exenteration (Ra-TPE) and intracorporeal ileal...
BACKGROUND: Diagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-code...
An increasing number of cancer patients are of advanced age as the incidence of cancer increases with age. In this article, the clinical predictors of...
Cancer therapeutics cause various treatment-related changes that may impact patient follow-up and disease monitoring. Although atypical responses such...
Intelligent and precision medical treatment is the future development trend of surgical operations. We proposed a core architecture of orthopedic robo...
MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs acquired between November 2019 and February 2020 ...