To avoid unnecessary surgical removal of lymph nodes in thyroid cancer patients, we would like to predict from thyroid whole slide images whether the tumor is aggressive or not. As a preparation to this goal, we would also like to predict the presence and location of […]
Hepatitis A Predictor We are working on hepatitis A prediction modeling. Details will be limited until the associated paper is published. Details provided on publication Details provided on publication https://medicine.ai.uky.edu/api/hepaa Github (private): https://github.com/codybum/hepa_a_pred Contact authors for model
COVID-19 Cell Detector Here are our results in a COVID-19 challenge hosted by telesto.ai. In this challenge the aim is to build a tool which is capable to diagnose COVID-19 (healthy or infected) from microscopic images of blood tests. The challenge provides a set of training […]
Soft Tissue B/M We are attempting to classify benign vs malignant in soft tissue slides. The training accuracy seems to improve, especially with the 1000 tiles data set. However, validation is another story. It is clear that nothing useful is being learned by the models. We […]
The computers do not know tissue from glass. Methods must be used to identify image regions (tiles) that contain tissue. Our efforts makes use of the excellent work: https://github.com/deroneriksson/python-wsi-preprocessing Process: -Apply filters for tissue segmentation -Mask out non-tissue by setting non-tissue pixels to 0 for their […]
We have been working with BERT[1], a natural language processing (NLP) AI model Google released a few years ago. BERT can be used for a number of NLP tasks, including multi-label classification. Using gross pathology reports, we have training our own language models using BERT to be used in […]
We have been working with BERT[1], a natural language processing (NLP) AI model Google released a few years ago. BERT can be used for a number of NLP tasks, including multi-label classification. I have been using BERT to determine the tissue type (part of determining case complexity for scheduling) from the […]