Publications by authors named "Yuval Globerson"
Article Synopsis
- The study aimed to assess the accuracy of a fully automated AI solution for interpreting HER2 immunohistochemistry (IHC) in breast cancer, acknowledging the need for more reliable HER2 scoring due to the effectiveness of HER2-targeted therapies.
- In a two-arm study involving 120 HER2 IHC whole-slide images and four surgical pathologists, the AI solution showed improved interobserver agreement and scoring accuracy compared to manual readings, particularly for distinguishing between HER2 0 and 1+ cases.
- The results indicate that the AI tool can enhance the consistency and reproducibility of HER2 scoring, supporting pathologists in following ASCO/CAP guidelines more effectively.
Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions.
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