Cancer
Transform discovery
How does Aiforia enable cancer research?
Aiforia’s deep learning AI platform has successfully enabled the automation of a versatile range of analyses in a number of areas and sample types such as in immuno-oncology, breast, prostate, lung, and testis.
With Aiforia you can automate the detection of relevant regions of interest based on morphology, use external ground-truths (e.g. treated vs non-treated groups) to find these regions in precise locations, and visualize the feature of interest.
Watch our webinar with MIT postdoc Peter Westcott:
Using AI to study non-small-cell lung carcinoma
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Solutions
Quantification
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Cancer biomarkers PD-L1, ER, Ki67 and HER2
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Tumor-infiltrating lymphocyte (TIL) percentage
Measurement
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Of spatial and morphological metrics
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Cell-to-tumor distance, for example: between stromal CD8+ cells and lung cancer tumor borders
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Cell-to-cell distances, including unique cell pairs (only the closest cells), for example: PD1 and PD-L1 pairing in lung stroma
Segmentation
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Multi-class segmentation
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Precise and quantitative grading of whole slide images
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Tumor grading and tumor burden
Regression
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Regression models predicting continuous values
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Cell and nucleus size, patient survival time and other end-points
