AIMC Topic: Neoplasms

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Integrating AI and RNA biomarkers in cancer: advances in diagnostics and targeted therapies.

Cell communication and signaling : CCS
Early detection and personalized treatment strategies are essential for enhancing patient outcomes, as cancer continues to be a significant cause of mortality on a global basis. In clinical practice, the identification and validation of reliable biom...

Towards scalable and cross-lingual specialist language models for oncology.

Scientific reports
Clinical oncology generates vast, unstructured data that often contain inconsistencies, missing information, and ambiguities, making it difficult to extract reliable insights for data-driven decision-making. General-purpose large language models (LLM...

Pan-cancer single-cell and spatial transcriptomics implicate cancer-associated fibroblasts in neutrophil immunosuppressive phenotypic transitions and immunotherapy resistance.

Functional & integrative genomics
Neutrophils are the most abundant granulocyte population and have important functions such as defense against pathogens. However, they show significant Heterogeneity and play more complex roles in tumors. The theory of two-tiered differentiation of n...

Quality of Cancer-Related Information on New Media (2014-2023): Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: New media have become vital sources of cancer-related health information. However, concerns about the quality of that information persist.

Spatial proteomics for investigating solid tumor resistance mechanisms.

Cancer metastasis reviews
Spatial proteomics technologies have been pivotal in profiling tumor immune microenvironments at single-cell resolution, advancing our understanding of cancer biology, identifying key cell populations in solid tumors, and predicting treatment respons...

Overcoming resistance to anti-PD-L1 immunotherapy: mechanisms, combination strategies, and future directions.

Molecular cancer
Cancer cells express high levels of programmed cell death-ligand 1 (PD-L1) to evade immune surveillance. PD-L1 interacts with PD-1 on T cells to make them non-functional. Thus, PD-L1 and PD-1 are pivotal targets in cancer immunotherapy. While anti-PD...

AutoTFCNNY: A multi-instance neural network for enhanced early cancer detection using TCR data.

PloS one
For most cancers, early diagnosis and intervention can significantly improve cure rates and patient survival. Consequently, achieving early and accurate cancer detection has always been a central focus in both medical practice and scientific research...

Peripheral blood multimodal integration via cross-attention for cancer immune profiling.

BMC cancer
OBJECTIVE: Accurate cancer risk prediction is hindered by complex, multi-layered immune interactions, and traditional tissue biopsies are invasive and lack scalability for large-scale or repeated assessments. Peripheral blood offers a minimally invas...

Cancer detection via one-shot learning: integrating gene expression and genomic mutation analysis.

BMC bioinformatics
BACKGROUND: Cancer is a complex disease influenced by numerous concurrent genetic factors that result in diverse tumor microenvironments (TMEs) across different cancer types. Large-scale genomic projects, such as The Cancer Genome Atlas, have undersc...

The Road to Precision Nanomedicine: An Insight on Drug Repurposing and Advances in Nanoformulations for Treatment of Cancer.

AAPS PharmSciTech
Cancer remains one of the most significant global health challenges, with its burden continuing to rise. The limitations of conventional anticancer therapies caused by the lack of tissue selectivity, demands urgent development of safer and more selec...