公开(公告)号：US20240194339A1

公开(公告)日：2024-06-13

申请号：US18286918

申请日：2022-05-27

Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA

Inventor： Nima Nassiri ,  Giovanni Cacciamani ,  Steven Cen ,  Vinay Duddalwar ,  Inderbir Gill ,  Darryl Hwang ,  Marissa Maas ,  Bino Varghese ,  Felix Yuh-Chern Yap

IPC: G16H50/20 ,  G06T7/00 ,  G06T7/40 ,  G06T7/62 ,  G16H30/40

CPC classification number: G16H50/20 ,  G06T7/0012 ,  G06T7/40 ,  G06T7/62 ,  G16H30/40 ,  G06T2207/10081 ,  G06T2207/10104 ,  G06T2207/10108 ,  G06T2207/20081 ,  G06T2207/30084 ,  G06T2207/30096

Abstract: A system, computer readable medium, apparatus and/or method for non-invasive, non-surgical, digital biopsy. The system, computer readable medium, apparatus and/or method accurately predicts benign kidney lesions from cancers in a patient. A processor may receive patient clinical factors, texture analysis of computer-tomographic imaging, and an artificial intelligence learning model. By implementing artificial intelligence, the processor may then predict or determine a probability of kidney cancer in the patient using the patient clinical factors, the texture analysis of computer-tomographic imaging, and the artificial intelligence learning model. Notably, the prediction is performed without needing invasive biopsy surgery and subsequent pathology analysis to arrive at a diagnosis but relies on radiomics metrics.