Cornelius Böhm
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View article: AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer
AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer Open
Risk stratification remains a critical challenge in non-small cell lung cancer patients for optimal therapy selection. In this study, we develop an artificial intelligence-powered spatial cellomics approach that combines histology, multipl…
View article: 1276 Leveraging artificial intelligence (AI) models delineating tumor vs immune cell expression for scalable biomarker analysis of clinical trial samples: a digital image analysis approach for NSCLC
1276 Leveraging artificial intelligence (AI) models delineating tumor vs immune cell expression for scalable biomarker analysis of clinical trial samples: a digital image analysis approach for NSCLC Open
Background Standard, manual, single-pathologist histopathology assessment in clinical trials makes accurate quantification of biomarkers expressed by both tumor and immune cells challenging due to inter-pathologist variability and non-exha…
View article: 970 Multiplex-immunofluorescence-based spatial characterization of the tumor-microenvironment of a large bicentric clinical non-small cell lung cancer cohort
970 Multiplex-immunofluorescence-based spatial characterization of the tumor-microenvironment of a large bicentric clinical non-small cell lung cancer cohort Open
Background Non-small-cell lung cancer (NSCLC) is the leading cause for cancer death. Current targeted- and immuno-therapies are effective in a patient subset, but causes for resistance and the complexity of the immune reaction are difficul…