Abstract: An artificial intelligence based vascular mapping and interventional procedure assisting platform configured to identify at least the femoral artery and the bifurcation point of the femoral artery of a patient based upon dynamic imaging of the patient. The platform may be a stroke management tool in which an angiogram and conventional bloodwork can be inputted into the platform and the platform provides one of i) classification of a stroke and stroke prediction; and whether an interventional procedure is indicated and wherein if interventional procedure is indicated then vascular mapping is provided with bifurcation points and the desired access illustrated together with a listing of accepted or counter indicated closure systems that may be used.

Abstract: A method of implementing an artificial intelligence based imaging platform for cardiopulmonary analysis comprises providing a multilayer convolutional network for cardiopulmonary analysis configured for segmenting data sets of cardiopulmonary scans into resolution voxels; supervised learning and validation of the platform by classification of tissue within classification voxels of a specific given training and validation data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of the training and validation data sets having a predetermined ground truth; and implementing the platform by classification of tissue within classification voxels of a specific given patient data sets by the multilayer convolutional network for cardiopulmonary analysis with each classification voxel of each data set assigned a label. An artificial intelligence based imaging platform implemented according to the method is disclosed.

Abstract: A method of implementing an artificial intelligence based neuroradiology platform for neurological tumor identification comprises providing a multilayer convolutional network for neurological tumor identification configured for segmenting data sets of full neurologic scans into resolution voxels; supervised learning and validation of the platform by classification of tissue within classification voxels of a specific given training and validation data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of the training and validation data sets having a predetermined ground truth; and implementing the platform by classification of tissue within classification voxels of a specific given patient data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of each data set assigned a label. The platform may be used for T-cell therapy initiation and tracking.