Gastric diffuse-type adenocarcinoma represents a disproportionately high percentage of cases of gastric cancers occurring in the young, and its relative incidence seems to be on the rise. Usually it affects the body of the stomach, and it presents shorter duration and worse prognosis compared with the differentiated (intestinal) type adenocarcinoma. The main difficulty encountered in the differential diagnosis of gastric adenocarcinomas occurs with the diffuse-type. As the cancer cells of diffuse-type adenocarcinoma are often single and inconspicuous in a background desmoplaia and inflammation, it can often be mistaken for a wide variety of non-neoplastic lesions including gastritis or reactive endothelial cells seen in granulation tissue. In this study we trained deep learning models to classify gastric diffuse-type adenocarcinoma from WSIs. We evaluated the models on five test sets obtained from distinct sources, achieving receiver operator curve (ROC) area under the curves (AUCs) in the range of 0.95–0.99. The highly promising results demonstrate the potential of AI-based computational pathology for aiding pathologists in their diagnostic workflow system.
Transdisciplinary artificial intelligence (AI) is programming/encoding/mapping/representing/modeling/simulating reality, physical, mental, social and digital, in computing machinery and robots, to effectively, efficiently and sustainably interact with the world.
“watch” is something we take for granted in our development cycle.
with each file change or save our app rebuilds/re-renders it self and we see the latest version. But there is a catch. the build…
Drawing an empty board to visualize the execution of shortest path algorithms.. “Shortest Path Algorithm (Part 1)” is published by Tiago Temporin in The Startup.
Python has become the most popular programming language among the developer community. Pertaining to its popularity, it has also found a great support in the Artificial Intelligence community with the implementation of high-level frameworks to run complex models easily. There has been tremendous development in domains such as computer vision & natural language processing and python libraries have caught up well with the latest advancements.
For a long time, setuptools and distutils were the only game in town when it came to creating Python packages, and both of these provided a simple enough interface: you write a setup.py file that invokes the setup() method,
It is possible to extend the functionality of Lowdefy beyond the framework's current capabilities by creating custom blocks, actions or operators. In this how-to example we will create a custom action to generate PDF documents client side or in the browser.
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