AIMC Topic: Neoplasms

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Interpretable graph Kolmogorov-Arnold networks for multi-cancer classification and biomarker identification using multi-omics data.

Scientific reports
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network...

Advancements in DNA methylation technologies and their application in cancer diagnosis.

Epigenetics
DNA methylation is a common epigenetic modification that maintains the integrity of the DNA sequence while profoundly influencing gene expression and phenotypic variation. Aberrant DNA methylation has been associated with the onset and progression of...

The evolving role of multimodal imaging, artificial intelligence and radiomics in the radiologic assessment of immune related adverse events.

Clinical imaging
Immunotherapy, in particular checkpoint blockade, has revolutionized the treatment of many advanced cancers. Imaging plays a critical role in assessing both treatment response and the development of immune toxicities. Both conventional imaging and mo...

Tumor microenvironment expressed enzymes (Matrix metalloproteinases, cathepsins, urokinase-type plasminogen activator) triggered polymersomes for liquid biopsy and cancer diagnostics: A review.

International journal of biological macromolecules
Enzyme-triggered polymersomes have emerged as a transformative platform in liquid biopsy and cancer diagnostics, enabling high-accuracy biomarker detection through precise enzymatic responsiveness. This review comprehensively examines the rational de...

Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells.

European journal of medical research
BACKGROUND: Cardioembolic stroke (CS) and atherosclerosis (AS) are closely related diseases. Ferroptosis, a novel form of programmed cell death, may play a key role in CS and AS. However, the pathophysiological mechanisms underlying their coexistence...

Beyond the native repertoire.

Science (New York, N.Y.)
Design of T cell receptors by artificial intelligence is poised to accelerate cancer immunotherapy.

Technological innovations promote cancer stem cell-based translational research.

Cancer letters
Cancer remains one of the leading causes of death worldwide, with therapy resistance and tumor recurrence driven by a subpopulation of cells known as cancer stem cells (CSCs). CSCs possess a remarkable ability to evade apoptosis, adapt to harsh micro...

Perceptions and Attitudes of Chinese Oncologists Toward Endorsing AI-Driven Chatbots for Health Information Seeking Among Patients with Cancer: Phenomenological Qualitative Study.

Journal of medical Internet research
BACKGROUND: Chatbots driven by large language model artificial intelligence (AI) have emerged as potential tools to enhance health information access for patients with cancer. However, their integration into patient education raises concerns among on...

Quantum Oncology: The Applications of Quantum Computing in Cancer Research.

Journal of medical systems
A global technological race is underway to develop increasingly powerful and precise quantum computers. As a transformative computing paradigm, quantum computing offers the potential for exponentially accelerating specific algorithms, thereby providi...

Recent advances in applying machine learning to proton radiotherapy.

Biomedical physics & engineering express
.: In radiation oncology, precision and timeliness of both planning and treatment are paramount values of patient care. Machine learning has increasingly been applied to various aspects of photon radiotherapy to reduce manual error and improve the ef...