浅谈人工智能在乳腺癌领域的应用进展
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摘要
人工智能是指由人工制造出来的系统所表现出来的智能,社会应用广泛。在医学领域,人工智能已经在医学影像、体外诊断、手术导航、智能康复、健康大数据等方面得到了实际的应用,并在提高癌症确诊率、加速新药研发、改善诊疗体验以及判断患者预后等方面都发挥了重要作用。目前,人工智能在乳腺癌领域的研究也有较多进展。因此,笔者简述了其在乳腺癌影像诊断、病理诊断以及辅助抗癌药物研发等方面的作用。
Artificial intelligence refers to intelligence exhibited by man-made machines, with widespread social application. In medicine,artificial intelligence has been applied in medical imaging,in vitro diagnosis,surgical navigation,intelligent rehabilitation and big data on healthcare, and has played an important role in increasing the diagnosis rate of cancer,accelerating the development of new drugs,improving the diagnosis and treatment experience of patients and predicting the patients 'prognosis. At present,the researches on artificial intelligence in breast cancer have made a lot of progress. We briefly summarized the application of artificial intelligence in imaging and pathological diagnosis of breast cancer and development of anti-cancer drugs.
Artificial intelligence refers to intelligence exhibited by man-made machines, with widespread social application. In medicine,artificial intelligence has been applied in medical imaging,in vitro diagnosis,surgical navigation,intelligent rehabilitation and big data on healthcare, and has played an important role in increasing the diagnosis rate of cancer,accelerating the development of new drugs,improving the diagnosis and treatment experience of patients and predicting the patients 'prognosis. At present,the researches on artificial intelligence in breast cancer have made a lot of progress. We briefly summarized the application of artificial intelligence in imaging and pathological diagnosis of breast cancer and development of anti-cancer drugs.
引文
[1]腾讯体育.三连败收官!柯洁再负Alpha Go人机大战遭零封[EB/OL].[2017-06-05].http://sports.qq.com/a/20170527/030772.htm.
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[3]Beura S,Majhi B,Dash R,et al.Classification of mammogram using two-dimensional discrete orthonormal S-transform for breast cancerdetection[J].Healthc Technol Lett,2015,2(2):46-51.
[4]Cheng HD,Shi XJ,Min R,et al.Approaches for automated detection and classification of masses in mammograms[J].Pattern R ecognit,2006,39(4):646-668.
[5]Mahersia H,Boulehmi H,Hamrouni K.Development of intelligent systems based on Bayesian regularization network and neuro-fuzzy models for mass detection in mammograms:a comparative analysis[J].Comput Methods Programs Biomed,2016,126:46-62.
[6]Parmeggiani D,Avenia N,Sanguinetti A,et al.Artificial intelligence against breast cancer(A.N.N.E.S-B.C.-Project)[J].Ann Ital Chir,2012,83(1):1-5.
[7]Patel TA,Puppala M,Ogunti R O,et al.Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods[J].Cancer,2017,123(1):114-121.
[8]No authors listed.Summary of safety and effectiveness[EB/OL].[2017-06-05].https://www.accessdata.fda.gov/cdrh_docs/pdf5/k050846.pdf.
[9]Chabi ML,Borget I,Ardiles R,et al.Evaluation of the accuracy of acomputer-aided diagnosis(CAD)system in breast ultrasound according to the radiologist’s experience[J].Acad R adiol,2012,19(3):311-319.
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[14]Wang D,Khosla A,Gargeya R,et al.Deep learning for identifying metastatic breast cancer[EB/OL].[2017-06-05].http://xueshu.baidu.com/s?wd=paperuri%3A%285cd6da92edd1ac337a8917bfaf22ec46%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Farxiv.org%2Fpdf%2F1606.05718&ie=utf-8&sc_us=17802863608197391119&qq-pf-to=pcqq.c2c.
[15]No authors listed.Our team transforming pathology together[EB/OL].[2017-06-05].https://pathai.com/team.html.
[16]Driessen H,Klink S.Philips and Path AI team up to improve breast cancer diagnosis using artificial intelligence technology in‘big data’pathology research[EB/OL].[2017-06-05].http://www.philips.com/a-w/about/news/archive/standard/news/press/2017/20170329-philips-andpathai-team-up-to-improve-breast-cancer-diagnosis.html.
[17]动脉网.解析Deep Care的人工智能算法,92.5%的乳腺癌诊断准确率是如何实现的?[EB/OL].[2017-06-05].http://vcbeat.net/35098.
[18]Fiuzy M,Haddadnia J,Mollania N,et al.Introduction of a new diagnostic method for breast cancer based on fine needle aspiration(FNA)test data and combining intelligent systems[J].Iran J Cancer Prev,2012,5(4):169-177.
[19]Subbaiah R M,Dey P,Nijhawan R.Artificial neural network in breast lesions from fine-needle aspiration cytology smear[J].Diagn Cytopathol,2014,42(3):218-224.
[20]No authors listed.Assisting pathologists in detecting cancer with deep learning[EB/OL].[2017-06-05].https://research.googleblog.com/2017/03/assistingpathologists-in-detecting.html.
[21]Douglas I.Cancer drug development time halved thanks to artificial intelligence[EB/OL].[2017-06-05].http://www.telegraph.co.uk/technology/news/11920393/Cancer-drug-development-time-halvedthanks-to-artificial-intelligence.html.
[22]Mullin E.Stopping breast cancer with help from AI[EB/OL].[2017-06-05].https://www.technologyreview.com/s/602721/stopping-breast-cancerwith-help-from-ai.
[23]No authors listed.IBM Watson health and broad institute launch major research initiative to study why cancers become drug resistant[EB/OL].[2017-06-05].https://www.broadinstitute.org/news/ibm-watson-health-andbroad-institute-launch-major-research-initiative-study-whycancers-become.
[24]Memorial Sloan-Kettering Cancer Center.IBMWatson and quest diagnostics launch genomic sequencing service using data from MSK[EB/OL].[2017-06-05].https://www.mskcc.org/about/innovative-collaborations/watson-oncology.
[25]IBM Watson Health.IBM Watson for genomics helps doctors give patients new hope[EB/OL].[2017-06-05].https://www.ibm.com/watson/health/oncologyand-genomics/genomics/.
[26]Somashekhar SP,Kumarc R,R authan A,et al.Abstract S6-07:Double blinded validation study to assess performance of IBM artificial intelligence platform,Watson for oncology in comparison with Manipal multidisciplinary tumour board-First study of 638 breast cancer cases[J].Cancer R es,2017,77(4):S16-S6-07.
[27]杭州认知网络科技有限公司.21家中国医院将应用IBM Watson肿瘤解决方案(IBM Watson for Oncology)助力医师提供个性化癌症诊疗[EB/OL].[2017-06-05].http://www.cognitivecare.cn/archives/210,2016-08-12.
[28]浙江省中医院新闻中心.携手成立沃森联合会诊中心,共同打造现代智慧医院---全国首家智能诊疗会诊中心落户我院[EB/OL].[2017-06-05].http://www.zjhtcm.com/Art/Art_2/Art_2_2376.aspx.
[29]Kim W,Kim KS,Lee JE,et al.Development of novel breast cancer recurrence prediction model using support vector machine[J].J Breast Cancer,2012,15(2):230-238.
[30]Kempowsky-Hamon T,Valle C,Lacroix-Triki M,et al.Fuzzy logic selection as a new reliable tool to identify molecular grade signatures in breast cancer--the INNODIAGstudy[J].BMC Med Genomics,2015,8:3.
[31]No authors listed.Innovative,personal early breast wellness screening[EB/OL].[2017-06-05].http://cyrcadiahealth.com/.
[32]中华人民共和国国务院.2017年政府工作报告[EB/OL].[2017-06-05].http://www.gov.cn/premier/2017-03/16/content_5177940.htm.
[2]No authors listed.R 2 Technology[EB/OL].[2017-06-05].http://www.r2tech.com/.
[3]Beura S,Majhi B,Dash R,et al.Classification of mammogram using two-dimensional discrete orthonormal S-transform for breast cancerdetection[J].Healthc Technol Lett,2015,2(2):46-51.
[4]Cheng HD,Shi XJ,Min R,et al.Approaches for automated detection and classification of masses in mammograms[J].Pattern R ecognit,2006,39(4):646-668.
[5]Mahersia H,Boulehmi H,Hamrouni K.Development of intelligent systems based on Bayesian regularization network and neuro-fuzzy models for mass detection in mammograms:a comparative analysis[J].Comput Methods Programs Biomed,2016,126:46-62.
[6]Parmeggiani D,Avenia N,Sanguinetti A,et al.Artificial intelligence against breast cancer(A.N.N.E.S-B.C.-Project)[J].Ann Ital Chir,2012,83(1):1-5.
[7]Patel TA,Puppala M,Ogunti R O,et al.Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods[J].Cancer,2017,123(1):114-121.
[8]No authors listed.Summary of safety and effectiveness[EB/OL].[2017-06-05].https://www.accessdata.fda.gov/cdrh_docs/pdf5/k050846.pdf.
[9]Chabi ML,Borget I,Ardiles R,et al.Evaluation of the accuracy of acomputer-aided diagnosis(CAD)system in breast ultrasound according to the radiologist’s experience[J].Acad R adiol,2012,19(3):311-319.
[10]Wood C.Computer aided detection(CAD)for breast M R I[J].Technol Cancer R es Treat,2005,4(1):49-53.
[11]Bttcher J,Renz DM,Zahm DM,et al.R esponse to neoadjuvant treatment of invasive ductal breast carcinomas including outcomeevaluation:M R I analysis by an automatic CAD system in comparison to visual evaluation[J].Acta Oncol,2014,53(6):759-768.
[12]Song SE,Seo BK,Cho K R,et al.Computeraided detection(CAD)system for breast M R I in assessment of local tumor extent,nodal status,and multifocality of invasive breast cancers:preliminary study[J].Cancer Imaging,2015,15:1.
[13]Liu Y,Gadepalli K,Norouzi M,et al.Detecting cancer metastases ongigapixel pathology images[EB/OL].[2017-06-05].http://www.datascienceassn.org/sites/default/files/Detecting%20Cancer%20 Metastases%20on%20Gigapixel%20Pathology%20Images.pdf.
[14]Wang D,Khosla A,Gargeya R,et al.Deep learning for identifying metastatic breast cancer[EB/OL].[2017-06-05].http://xueshu.baidu.com/s?wd=paperuri%3A%285cd6da92edd1ac337a8917bfaf22ec46%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Farxiv.org%2Fpdf%2F1606.05718&ie=utf-8&sc_us=17802863608197391119&qq-pf-to=pcqq.c2c.
[15]No authors listed.Our team transforming pathology together[EB/OL].[2017-06-05].https://pathai.com/team.html.
[16]Driessen H,Klink S.Philips and Path AI team up to improve breast cancer diagnosis using artificial intelligence technology in‘big data’pathology research[EB/OL].[2017-06-05].http://www.philips.com/a-w/about/news/archive/standard/news/press/2017/20170329-philips-andpathai-team-up-to-improve-breast-cancer-diagnosis.html.
[17]动脉网.解析Deep Care的人工智能算法,92.5%的乳腺癌诊断准确率是如何实现的?[EB/OL].[2017-06-05].http://vcbeat.net/35098.
[18]Fiuzy M,Haddadnia J,Mollania N,et al.Introduction of a new diagnostic method for breast cancer based on fine needle aspiration(FNA)test data and combining intelligent systems[J].Iran J Cancer Prev,2012,5(4):169-177.
[19]Subbaiah R M,Dey P,Nijhawan R.Artificial neural network in breast lesions from fine-needle aspiration cytology smear[J].Diagn Cytopathol,2014,42(3):218-224.
[20]No authors listed.Assisting pathologists in detecting cancer with deep learning[EB/OL].[2017-06-05].https://research.googleblog.com/2017/03/assistingpathologists-in-detecting.html.
[21]Douglas I.Cancer drug development time halved thanks to artificial intelligence[EB/OL].[2017-06-05].http://www.telegraph.co.uk/technology/news/11920393/Cancer-drug-development-time-halvedthanks-to-artificial-intelligence.html.
[22]Mullin E.Stopping breast cancer with help from AI[EB/OL].[2017-06-05].https://www.technologyreview.com/s/602721/stopping-breast-cancerwith-help-from-ai.
[23]No authors listed.IBM Watson health and broad institute launch major research initiative to study why cancers become drug resistant[EB/OL].[2017-06-05].https://www.broadinstitute.org/news/ibm-watson-health-andbroad-institute-launch-major-research-initiative-study-whycancers-become.
[24]Memorial Sloan-Kettering Cancer Center.IBMWatson and quest diagnostics launch genomic sequencing service using data from MSK[EB/OL].[2017-06-05].https://www.mskcc.org/about/innovative-collaborations/watson-oncology.
[25]IBM Watson Health.IBM Watson for genomics helps doctors give patients new hope[EB/OL].[2017-06-05].https://www.ibm.com/watson/health/oncologyand-genomics/genomics/.
[26]Somashekhar SP,Kumarc R,R authan A,et al.Abstract S6-07:Double blinded validation study to assess performance of IBM artificial intelligence platform,Watson for oncology in comparison with Manipal multidisciplinary tumour board-First study of 638 breast cancer cases[J].Cancer R es,2017,77(4):S16-S6-07.
[27]杭州认知网络科技有限公司.21家中国医院将应用IBM Watson肿瘤解决方案(IBM Watson for Oncology)助力医师提供个性化癌症诊疗[EB/OL].[2017-06-05].http://www.cognitivecare.cn/archives/210,2016-08-12.
[28]浙江省中医院新闻中心.携手成立沃森联合会诊中心,共同打造现代智慧医院---全国首家智能诊疗会诊中心落户我院[EB/OL].[2017-06-05].http://www.zjhtcm.com/Art/Art_2/Art_2_2376.aspx.
[29]Kim W,Kim KS,Lee JE,et al.Development of novel breast cancer recurrence prediction model using support vector machine[J].J Breast Cancer,2012,15(2):230-238.
[30]Kempowsky-Hamon T,Valle C,Lacroix-Triki M,et al.Fuzzy logic selection as a new reliable tool to identify molecular grade signatures in breast cancer--the INNODIAGstudy[J].BMC Med Genomics,2015,8:3.
[31]No authors listed.Innovative,personal early breast wellness screening[EB/OL].[2017-06-05].http://cyrcadiahealth.com/.
[32]中华人民共和国国务院.2017年政府工作报告[EB/OL].[2017-06-05].http://www.gov.cn/premier/2017-03/16/content_5177940.htm.