JPMA. The Journal of the Pakistan Medical Association
Apr 1, 2024
Image learning involves using artificial intelligence (AI) to analyse radiological images. Various machine and deeplearning- based techniques have been employed to process images and extract relevant features. These can later be used to detect tumour...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
The delivery of effective targeted therapies requires comprehensive analyses of the molecular profiling of tumors and matching with clinical phenotypes in the context of existing knowledge described in biomedical literature, registries, and knowledge...
The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be ...
Artificial Intelligence (AI) algorithms have shown great promise in oncological imaging, outperforming or matching radiologists in retrospective studies, signifying their potential for advanced screening capabilities. These AI tools offer valuable su...
The practice of oncology requires analyzing and synthesizing abundant data. From the patient's workup to determine eligibility to the therapies received to the post-treatment surveillance, practitioners must constantly juggle, evaluate, and weigh dec...
PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the field of clinical oncology, including early diagnosis of disease, local staging, detection of systemic metastases, evaluation of treatment efficacy a...
Gan to kagaku ryoho. Cancer & chemotherapy
Sep 1, 2023
The tumor immune microenvironment(TIME)of colorectal cancer contains indicators of unique therapeutic outcomes for each cancer patient. Deep learning-based imaging cytometry(DL-IC), which can obtain objective and reproducible cell- related informatio...
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