AIMC Topic: Medical Oncology

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Artificial intelligence for nuclear medicine in oncology.

Annals of nuclear medicine
As in all other medical fields, artificial intelligence (AI) is increasingly being used in nuclear medicine for oncology. There are many articles that discuss AI from the viewpoint of nuclear medicine, but few focus on nuclear medicine from the viewp...

Artificial intelligence in oncology: current applications and future perspectives.

British journal of cancer
Artificial intelligence (AI) is concretely reshaping the landscape and horizons of oncology, opening new important opportunities for improving the management of cancer patients. Analysing the AI-based devices that have already obtained the official a...

Deep learning in cancer diagnosis, prognosis and treatment selection.

Genome medicine
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across health...

A deep look into radiomics.

La Radiologia medica
Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into ...

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.

Journal of clinical epidemiology
OBJECTIVE: Evaluate the completeness of reporting of prognostic prediction models developed using machine learning methods in the field of oncology.

Potential and limitations of radiomics in neuro-oncology.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Radiomics seeks to apply classical methods of image processing to obtain quantitative parameters from imaging. Derived features are subsequently fed into algorithmic models to aid clinical decision making. The application of radiomics and machine lea...

Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

Journal of clinical pathology
Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing number of complex biomarkers contributes to costly and delayed decision-making in routine oncology care and treatment. As cancer is expected to rank a...