Pathology on chriswalsh.devhttps://chriswalsh.dev/categories/pathology/Recent content in Pathology on chriswalsh.devHugoen-usSun, 19 Jun 2022 23:00:00 +0000Ensuring accurate staining with deep generative networks for virtual IHC in pathology.https://chriswalsh.dev/publications/ensuring-accurate-stain-reproduction-in-pathology/Sun, 19 Jun 2022 23:00:00 +0000https://chriswalsh.dev/publications/ensuring-accurate-stain-reproduction-in-pathology/Abstract : Immunohistochemistry is a valuable diagnostic tool for cancer pathology. However, it requires specialist labs and equipment, is time-intensive, and is difficult to reproduce. Consequently, a long term aim is to provide a digital method of recreating physical immunohistochemical stains. Generative Adversarial Networks have become exceedingly advanced at mapping one image type to another and have shown promise at inferring immunostains from haematoxylin and eosin. However, they have a substantial weakness when used with pathology images as they can fabricate structures that are not present in the original data.Evolution of Convolutional Neural Networks for Lymphoma Classification.https://chriswalsh.dev/publications/evolution-of-convolutional-neural-networks-for-lymphoma-classification-copy/Mon, 01 Mar 2021 00:00:00 +0000https://chriswalsh.dev/publications/evolution-of-convolutional-neural-networks-for-lymphoma-classification-copy/Abstract : Lymphoma comprises over 60 subtypes, typically requiring specialized pathologists for accurate diagnosis. Our study aimed to evaluate the efficacy of Artificial Neural Networks (ANNs) and Deep Learning in Lymphoma classification, while also assessing the optimization potential of Evolutionary Algorithms (EAs). Utilizing TensorFlow and Keras for network construction, we developed an innovative framework to evolve network weights. The optimal model, a Convolutional Neural Network (CNN), achieved a tenfold cross-validation test accuracy of 95.It's Good to Chat?: Evaluation and Design Guidelines for Combining Open-Domain Social Conversation with Task-Based Dialogue in Intelligent Buildings.https://chriswalsh.dev/publications/its-good-to-chat/Mon, 19 Oct 2020 00:00:00 +0000https://chriswalsh.dev/publications/its-good-to-chat/Abstract : We present and evaluate a deployed conversational AI system that acts as a host of a working public building on a university campus. The system combines open-domain social chat with task-based conversation regarding navigation in the building, live resource updates (e.g. available computers), and events in the building. We investigated the impact of open-domain social chat on task completion and user preferences by comparing the combined system with a task-only version.