Fuzzy graph theory, with its ability to handle uncertainty and varying relationship strengths, offers a powerful tool for modeling and solving complex problems across diverse fields like medical, social network, biological networks, etc. The topologi...
Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based...
BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into several health care sectors, including medical imaging. AI can transform how medical imaging is conducted and interpreted, especially in cardio-oncology.
Cancer immunology, immunotherapy : CII
May 9, 2025
PURPOSE: The aim of this study is to better characterize the clinical characteristics and outcomes of patients diagnosed with Immune checkpoint Inhibitor (ICI) pneumonitis and propose predictive models.
Analysis of volatile organic compounds by electronic nose (e-nose) may address gaps in non-invasive screening for neoplasia. Machine learning impacts study design and sample size requirements, but guidance on clinical study design is limited. This st...
BACKGROUND: Artificial intelligence (AI) is a promising tool used in oncology that may be able to facilitate diagnosis, treatment planning, and patient management. Transparency and completeness of protocols of randomized controlled trials (RCT) invol...
BACKGROUND: Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understand...
MOTIVATION: Feature selection is a critical task in machine learning and statistics. However, existing feature selection methods either (i) rely on parametric methods such as linear or generalized linear models, (ii) lack theoretical false discovery ...
Artificial intelligence could enhance chimeric antigen receptor T-cell therapy outcomes through optimization of all steps, from target identification, vector design, and manufacturing to personalized data-driven clinical decisions. In this report, we...
Antibody-drug conjugates (ADCs) have revolutionized the field of cancer treatment in the era of precision medicine due to their ability to precisely target cancer cells and release highly effective drugs. Nevertheless, the rational design and discove...
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