AI Medical Compendium Topic

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Tumor Microenvironment

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Perspectives in pathomics in head and neck cancer.

Current opinion in oncology
PURPOSE OF REVIEW: Pathology is the cornerstone of cancer care. Pathomics, which represents the use of artificial intelligence in digital pathology, is an emerging and promising field that will revolutionize medical and surgical pathology in the comi...

Artificial Intelligence Will Not Replace Health Professionals, but the Proper Use of Artificial Intelligence Will Make Health Professionals Better.

Cancer research
Deep learning has enabled great advances to be made in cancer research with regards to diagnosis, prognosis, and treatment. The study by Wang and colleagues in this issue of develops a deep learning algorithm with the ability to digitally stain hist...

Deep Learning Reveals Cancer Metastasis and Therapeutic Antibody Targeting in the Entire Body.

Cell
Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipelin...

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cell
Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovati...

Identification of topological features in renal tumor microenvironment associated with patient survival.

Bioinformatics (Oxford, England)
MOTIVATION: As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However, traditional qualitative and/...