Artificial Intelligence in Revolutionizing Kidney Care and Beyond:Kid-AI Revolution  

作　　者：Kounaina Khan Farhan Zameer Pratheek Jain Ravi KR Vidya Niranjan Manoj S Ravish H Subrahmanya Padyana 

机构地区：[1]PathoGutOmics Laboratory,Alva’s Traditional Medicinal Archive(ATMA),Department of Ayurveda Pharmacology,Alva’s Ayurveda Medical College,Vidyagiri,Moodubidire 574227,Dakshina Kannada,Karnataka,India [2]Sahyadri Narayana Multispeciality Hospital,Shivamogga 577202,Karnataka,India [3]Department of Biotechnology,RV College of Engineering,Kengeri,Bengaluru 560059,Karnataka,India [4]Cognimuse Pvt Ltd,Incubated Under Atal Incubation Center,Nitte University,Karkala 574110,Karnataka,India [5]Department of Neurochemistry,National Institute of Mental Health and Neuro Sciences(NIMHANS),Bengaluru 560029,Karnataka,India

出　　处：《Journal of Bio-X Research》2024年第4期182-195,共14页生物组学研究杂志(英文)

摘　　要：Recent advancements in artificial intelligence(AI)have significantly impacted the diagnosis and treatment of kidney diseases,offering novel approaches for precise quantitative assessments of nephropathology.The collaboration between computer engineers,renal specialists,and nephropathologists has led to the development of AI-assisted technology,presenting promising avenues for renal pathology diagnoses,disease prediction,treatment effectiveness assessment,and outcome prediction.This review provides a comprehensive overview of AI applications in renal pathology,focusing on computer vision algorithms for kidney structure segmentation,specific pathological changes,diagnosis,treatment,and prognosis prediction based on images along with the role of machine learning(ML)and deep learning(DL)in addressing global public health issues related to various nephrological conditions.Despite the transformative potential,the review acknowledges challenges such as data privacy,interpretability of AI models,the imperative need for trust in AI-driven recommendations for broad applicability,external validation,and improved clinical decision-making.Overall,the ongoing integration of AI technologies in nephrology paves the newer way for more precise diagnostics,personalized treatments,and improved patient care outcome.

关 键 词：kidney diseases artificial intelligence ai machine learning computer vision deep learning artificial intelligence predictiontreatment effectiveness assessmentand 

分 类 号：R692[医药卫生—泌尿科学]