机器学习在脊柱疾病智能诊治中的应用综述

doi:10.11896/jsjkx.201100006

Abstract

Abstract: Spine diseases are prevalent in modern society.The diagnosis and treatment mainly depend on doctors' professional knowledge and clinical experience.More and more patients and conventional treatments resulted in heavy overload and inefficient diagnosis.Machine learning algorithms can automatically extract useful information from datasets and images,assisting doctors to locate the lesion and carry out the accurate treatment.This paper focuses on the applications of machine learning in the field of spine disease and summarizes the relevant research from aspects of datasets,feature selection,model,evaluation metrics,and so on.Firstly,in terms of machine learning algorithms,the utility of some typical algorithms in disease diagnosis and treatment is described.Moreover,in terms of the actual applications of disease diagnosis and treatment(risk factor analysis and disease prediction,disease recognition and classification,feature extraction of spine image and image segmentation),the performances of several important models are compared in some specific experiments.Accuracy,specificity,sensitivity,AUC,and other evaluation indexes are involved.Finally,the major limitations and corresponding issues in current applications are summarized.

Key words: Machine learning, Neural network, Review, Smart health-care, Spine disease

CLC Number:

TP399

LIU Tong-tong, YANG Huan, XI Yong-ming, GUO Jian-wei, PAN Zhen-kuan, HUANG Bao-xiang. Review on Intelligent Diagnosis of Spine Disease Based on Machine Learning[J].Computer Science, 2021, 48(11A): 597-607.

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