医学智能影像的应用前景与发展困境综述
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摘要
医学智能影像高效、客观、精准,加之政府支持、资本投入、技术进步使得我国医学智能影像产业在近几年有所发展,市场前景广阔,但目前医学智能影像相较于传统医学影像在市场上尚处于劣势。基于对医学智能影像市场运作模式的分析以及通过PEST分析方法,本文探讨了影响医学智能影像产业发展的障碍影响因素。研究发现,市场主体中的政府和企业主体存在诸多不足之处,未能更好地满足市场上对医学智能影像的消费者需求,其中技术局限、无配套法律法规等障碍影响因素制约了医学智能影像的发展,消费者需求程度随着两个主体解决障碍影响因素的增多而增大。
It is well known that artificial intelligence medical image(AIMI) is efficient, objective and accurate. In addition, with government support, capital investment and technological progress, the AIMI of China industry has developed in recent years,with broad market prospects. However, the AIMI still in a disadvantage state comparing with the traditional MI field. Based on the analysis of the operation mode of the medical intelligent image market and the PEST analysis method, the obstacles affecting the development of the AIMI industry were discussed in this paper. The study found that the government and enterprises had many shortcomings in the market, which failed to better meet the market demand for medical intelligent imaging. Among them, technical limitations, no supporting laws and regulations and other obstacles restricted the development of medical intelligent imaging. The degree of consumer demand increased with the increasing of the two main factors to solve the obstacle.
It is well known that artificial intelligence medical image(AIMI) is efficient, objective and accurate. In addition, with government support, capital investment and technological progress, the AIMI of China industry has developed in recent years,with broad market prospects. However, the AIMI still in a disadvantage state comparing with the traditional MI field. Based on the analysis of the operation mode of the medical intelligent image market and the PEST analysis method, the obstacles affecting the development of the AIMI industry were discussed in this paper. The study found that the government and enterprises had many shortcomings in the market, which failed to better meet the market demand for medical intelligent imaging. Among them, technical limitations, no supporting laws and regulations and other obstacles restricted the development of medical intelligent imaging. The degree of consumer demand increased with the increasing of the two main factors to solve the obstacle.
引文
[1]张蓝飞.人工智能突破影像设备软硬件局限[N].医药经济报,2017-08-07(11).
[2]Ramesh AN,Kambhampati C,Monson JR,et al.Artificial Intelligence in Medicine[J].Artif Intell Med,2004,7(5):334-338.
[3]王弈,李传富.人工智能方法在医学图像处理中的研究新进展[J]中国医学物理学杂志,2013,(3):4139-4142.
[4]罗诚,何琦.基于人工智能的智慧医疗发展现状及其伦理问题初探[J].经贸实践,2018,(9):218-220.
[5]沈玉姗.AI医疗的中国式困境[J].21世纪商业评论,2017(10):42-47.
[6]沈伟富,徐旭,何炜.云影像技术应用与思考[J].医学信息学杂志,2018,(3):36-40.
[7]Xu K,Ba J,Kiros R,et al.Show,attend and tell:Neural image caption generation with visual attention[J].Comput Sci2015:2048-2057.
[8]卢光明,张志强.人工智能医学影像[J].医学研究生学报,2018,(7):683-687.
[9]陈红霞,李阳雪.医学影像+人工智能渐行渐近数据处理难题待解[N].21世纪经济报道,2017-09-08(16).
[10]戈晶晶.中国人工智能需要新生态圈[J].中国信息界,2018,(2):52-53.
[11]李芳晨.AI撬动医疗:人工智能的初探与实践[J].中国医院院长,2017,(24):38-41.
[12]王海星,田雪晴.人工智能在医疗领域应用现状、问题及建议[J]卫生软科学,2018,(5):4-9.
[13]于观贞,刘西洋,张彦春,等.人工智能在临床医学中的应用与思考[J].第二军医大学学报,2018,(4):359-365.
[14]吉浩,曾凡荣,赵亚妮,等.人工智能在医疗影像诊断领域的研究进展[J].大医生,2017,(8):127-129.
[15]金征宇.前景与挑战:当医学影像遇见人工智能[J].协和医院杂志,2018,(1):2-4.
[16]金振娅.“互联网+医疗健康”:医疗质量如何保障?[J].中国设备工程,2018,(9):8-10.
[17]邱超奕.聚焦医疗人工智能:辅助医疗,减少误诊漏诊[J].决策探索,2018,(3):28-29.
[2]Ramesh AN,Kambhampati C,Monson JR,et al.Artificial Intelligence in Medicine[J].Artif Intell Med,2004,7(5):334-338.
[3]王弈,李传富.人工智能方法在医学图像处理中的研究新进展[J]中国医学物理学杂志,2013,(3):4139-4142.
[4]罗诚,何琦.基于人工智能的智慧医疗发展现状及其伦理问题初探[J].经贸实践,2018,(9):218-220.
[5]沈玉姗.AI医疗的中国式困境[J].21世纪商业评论,2017(10):42-47.
[6]沈伟富,徐旭,何炜.云影像技术应用与思考[J].医学信息学杂志,2018,(3):36-40.
[7]Xu K,Ba J,Kiros R,et al.Show,attend and tell:Neural image caption generation with visual attention[J].Comput Sci2015:2048-2057.
[8]卢光明,张志强.人工智能医学影像[J].医学研究生学报,2018,(7):683-687.
[9]陈红霞,李阳雪.医学影像+人工智能渐行渐近数据处理难题待解[N].21世纪经济报道,2017-09-08(16).
[10]戈晶晶.中国人工智能需要新生态圈[J].中国信息界,2018,(2):52-53.
[11]李芳晨.AI撬动医疗:人工智能的初探与实践[J].中国医院院长,2017,(24):38-41.
[12]王海星,田雪晴.人工智能在医疗领域应用现状、问题及建议[J]卫生软科学,2018,(5):4-9.
[13]于观贞,刘西洋,张彦春,等.人工智能在临床医学中的应用与思考[J].第二军医大学学报,2018,(4):359-365.
[14]吉浩,曾凡荣,赵亚妮,等.人工智能在医疗影像诊断领域的研究进展[J].大医生,2017,(8):127-129.
[15]金征宇.前景与挑战:当医学影像遇见人工智能[J].协和医院杂志,2018,(1):2-4.
[16]金振娅.“互联网+医疗健康”:医疗质量如何保障?[J].中国设备工程,2018,(9):8-10.
[17]邱超奕.聚焦医疗人工智能:辅助医疗,减少误诊漏诊[J].决策探索,2018,(3):28-29.