The goal of Artificial Intelligence Resource (AIR) is to make AI tools available to Clinical Cancer Research (CCR) investigators. The strength of AI is that algorithms can be trained to seek specific information that may scientifically or clinically important. AIR will mainly focus on “Computer Vision” which analyzes medical images, such as radiologic, digital pathology, video/endoscopy and optical imaging among others. Examples of potential projects include developing better screening, detection methods or predictive markers, or improving procedures among many others. Both clinical and laboratory-based imaging projects will be considered.
Multiresolution Application of Artificial Intelligence in Digital Pathology for Prediction of Positive Lymph Nodes From Primary Tumors in Bladder Cancer.
Objective: to develop an artificial intelligence (AI)-based model for identifying patients with lymph node (LN) metastasis based on digital evaluation of primary tumors. Link to publication: PMID 32330067
Detection of prostate cancer in multiparametric MRI using random forest with instance weighting.
Objective: prostate computer-aided diagnosis (CAD) based on random forest to detect prostate cancer using a combination of spatial, intensity, and texture features extracted from three sequences, T2W, ADC, and B2000 images.