AIMC Topic: Biomarkers, Tumor

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Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.

BMC cancer
BACKGROUND: A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study was to ident...

Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell lines.

Scientific reports
Computational models for drug sensitivity prediction have the potential to significantly improve personalized cancer medicine. Drug sensitivity assays, combined with profiling of cancer cell lines and drugs become increasingly available for training ...

Identification of Tissue of Origin and Guided Therapeutic Applications in Cancers of Unknown Primary Using Deep Learning and RNA Sequencing (TransCUPtomics).

The Journal of molecular diagnostics : JMD
Cancers of unknown primary (CUP) are metastatic cancers for which the primary tumor is not found despite thorough diagnostic investigations. Multiple molecular assays have been proposed to identify the tissue of origin (TOO) and inform clinical care;...

Integrating ensemble systems biology feature selection and bimodal deep neural network for breast cancer prognosis prediction.

Scientific reports
Breast cancer is a heterogeneous disease. To guide proper treatment decisions for each patient, robust prognostic biomarkers, which allow reliable prognosis prediction, are necessary. Gene feature selection based on microarray data is an approach to ...

The impact of site-specific digital histology signatures on deep learning model accuracy and bias.

Nature communications
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and dri...

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

Virchows Archiv : an international journal of pathology
The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserve...

[Artificial intelligence, radiomics and pathomics to predict response and survival of patients treated with radiations].

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Artificial intelligence approaches in medicine are more and more used and are extremely promising due to the growing number of data produced and the variety of data they allow to exploit. Thus, the computational analysis of medical images in particul...