疾病預(yù)后常受到多種因素影響,且各因素之間又存在著復(fù)雜的非線性關(guān)系。人工神經(jīng)網(wǎng)絡(luò)(artificial neural network,ANN)是一種模擬生物神經(jīng)元工作方式的人工智能模型,具有較強智能化處理多因素非線性能力。目前神經(jīng)網(wǎng)絡(luò)模型越來越多地應(yīng)用于臨床醫(yī)學(xué)領(lǐng)域,特別是疾病預(yù)后的預(yù)測。我們就人工神經(jīng)網(wǎng)絡(luò)的基本原理及其在疾病預(yù)后研究方面的應(yīng)用進(jìn)行綜述。
引用本文: 陳杰,周勤,陳進(jìn),石應(yīng)康,董力. 人工神經(jīng)網(wǎng)絡(luò)在疾病預(yù)后研究中的應(yīng)用進(jìn)展. 中國胸心血管外科臨床雜志, 2013, 20(1): 95-99. doi: 復(fù)制
1. | 蔣宗禮, 主編. 人工神經(jīng)網(wǎng)絡(luò)導(dǎo)論. 北京:高等教育出版社, 2001. 7-10. |
2. | 叢爽, 面向, 主編. MATLAB 工具箱的神經(jīng)網(wǎng)絡(luò)理論與應(yīng)用. 第3版. 合肥:中國科技技術(shù)大學(xué)出版社, 2009. 1-7. |
3. | 方積乾, 陸盈, 主編. 現(xiàn)代醫(yī)學(xué)統(tǒng)計學(xué). 北京:人民衛(wèi)生出版社, 2002. 708-709. |
4. | 韓立群, 主編. 人工神經(jīng)網(wǎng)絡(luò)教程. 北京:北京郵電大學(xué)出版社, 2006. 4-5. |
5. | Advantages TJ. Disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J Clin Epidemiol, 1996, 49 (11):1225-1231. |
6. | 陳進(jìn), 石應(yīng)康, 董力. 疾病預(yù)后因素研究設(shè)計在心臟瓣膜置換術(shù)后抗凝治療臨床研究中的應(yīng)用. 中國胸心血管外科臨床雜志, 2011, 18 (4):286-288. |
7. | 王家良, 王波, 主編. 臨床流行病學(xué):臨床科研設(shè)計, 測量與評價. 第3版. 上海:上??茖W(xué)技術(shù)出版社, 2009. 434-435. |
8. | 孫振球, 徐勇勇, 主編. 醫(yī)學(xué)衛(wèi)生統(tǒng)計. 第3版. 北京:人民衛(wèi)生出版社, 2010. 318. |
9. | Mcculloch WS, Pitts W. A logical calculus of the ideas immanent in nervous activity. Bull Math Biol, 1990, 52 (1â):99-115. |
10. | Minsky M, Papert S, Chief editor. Perceptron (expanded edition). Cambridge, MA:MIT Press, 1988. 1969. |
11. | Rumelhart D, Hintont GE, Williams RJ. Learning representations by back-propagating errors. Nature, 1986, 323 (9):533-536. |
12. | 施彥, 韓力群, 廉小親, 主編. 神經(jīng)網(wǎng)絡(luò)設(shè)計方法與實例分析. 北京:北京郵電大學(xué)出版社, 2009. 307-361. |
13. | Peng SY, Peng SK. Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks. Anaesthesia, 2008, 63 (7):705-713. |
14. | Akl A, Ismail AM, Ghoneim M. Prediction of graft survival of living-donor kidney transplantation:nomograms or artificial neural networks ? Transplantation, 2008, 86 (10):1401-1406. |
15. | Nilsson J, Ohlsson M, Thulin L, et al. Risk factor identification and mortality prediction in cardiac surgery using artificial neural networks. J Thorac Cardiovasc Surg, 2006, 132 (1):12-19. |
16. | Nashef S, Roques F, Hammill BG, et al. Validation of European system for cardiac operative risk evaluation (EuroSCORE)in North American cardiac surgery. Eur J Cardio-thoracic Surg, 2002, 22 (1):101-105. |
17. | Gogbashian A, Sedrakyan A, Treasure T. Euroscore:a systematic review of international performance. Euro J Cardio-thoracic Surg, 2004, 25 (5):695-700. |
18. | Yoshimura M, Takahashi Y, Uchida K, et al. Prediction of survival in prostate cancer patients by bone scan index using computer-assisted diagnosis system. Eur J Nucl Med Mol Imaging, 2011, 38 (Suppl 2):S414. |
19. | Scholl S, Biã¨che I, Pallud C, et al. Relevance of multiple biological parameters in breast cancer prognosis. Breast, 1996, 5 (1):21-30. |
20. | Ei MM, Akl A, Mosbah A, et al. Prediction of survival after radical cystectomy for invasive bladder carcinoma:risk group stratification, nomograms or artificial neural networks?J Urol, 2009, 182 (2):466-472. |
21. | 袁金秋, 劉雅莉, 楊克虎. 基于人工神經(jīng)網(wǎng)絡(luò)的數(shù)據(jù)挖掘技術(shù)在臨床中應(yīng)用進(jìn)展. 圖書與情報, 2010 (3):95-98. |
22. | 范炤, 呂吉元, 陳澤華, 等. 基于BP人工神經(jīng)網(wǎng)絡(luò)的急性前壁心肌梗塞冠脈內(nèi)支架術(shù)一年預(yù)后模型研究. 中國衛(wèi)生統(tǒng)計, 2010, 27 (1):71-73, 82. |
23. | 張鳴. 初步構(gòu)建基于我國肝移植受體的生存評估模型及其與MELD的比較研究. 成都:四川大學(xué), 2006. 1-87. |
24. | 蔡煜東, 官家文, 甘駿人, 等. 人工神經(jīng)網(wǎng)絡(luò)方法在乳腺癌死亡率研究中的應(yīng)用. 中國生物醫(yī)學(xué)工程學(xué)報, 1994, 13 (4):364-366. |
25. | 黃德生, 周寶森, 劉延齡, 等. BP人工神經(jīng)網(wǎng)絡(luò)用于肺鱗癌預(yù)后預(yù)測. 中國衛(wèi)生統(tǒng)計, 2000, 17 (6):337-340. |
26. | 姜成華, 王正國, 朱佩芳, 等. 基于神經(jīng)網(wǎng)絡(luò)的創(chuàng)傷預(yù)后仿真模型. 中華創(chuàng)傷雜志, 1997, 13 (3):42-44. |
27. | De Laurentiis M, De Placido S, Bianco AR, et al. A prognostic model that makes quantitative estimates of probability of relapse for breast cancer patients. Clin Cancer Res, 1999, 5 (12):4133-4139. |
28. | Piaggi P, Lippi C, Fierabracci P, et al. Artificial neural networks in the outcome prediction of adjustable gastric banding in obese women. PLoS One, 2010, 5 (10):e13624. |
29. | Tu JV, Guerriere MJ. Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Comput Biomed Res, 1993, 26 (3):220-229. |
30. | Lin E, Hwang Y, Wang SC, et al. An artificial neural network approach to the drug efficacy of interferon treatments. Pharmacogenomics, 2006, 7 (7):1017-1024. |
31. | Chang HH, Chen PS, Giacomini KM. A neural network model for predicting treatment response of antidepressant in patients with major depressive disorder. Biol Psychiatry, 2012, 71 (8):286S. |
32. | Solomon I, Maharshak N, Chechik G, et al. Applying an artificial neural network to warfarin maintenance dose prediction. Isr Med Assoc J, 2004, 6 (12):732-735. |
33. | Dipti I, Peter BS, Almassy RJ, et al. Artificial neural networks:Current status in cardiovascular medicine. J Am Coll Cardiol, 1996, 28 (2):515-521. |
- 1. 蔣宗禮, 主編. 人工神經(jīng)網(wǎng)絡(luò)導(dǎo)論. 北京:高等教育出版社, 2001. 7-10.
- 2. 叢爽, 面向, 主編. MATLAB 工具箱的神經(jīng)網(wǎng)絡(luò)理論與應(yīng)用. 第3版. 合肥:中國科技技術(shù)大學(xué)出版社, 2009. 1-7.
- 3. 方積乾, 陸盈, 主編. 現(xiàn)代醫(yī)學(xué)統(tǒng)計學(xué). 北京:人民衛(wèi)生出版社, 2002. 708-709.
- 4. 韓立群, 主編. 人工神經(jīng)網(wǎng)絡(luò)教程. 北京:北京郵電大學(xué)出版社, 2006. 4-5.
- 5. Advantages TJ. Disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J Clin Epidemiol, 1996, 49 (11):1225-1231.
- 6. 陳進(jìn), 石應(yīng)康, 董力. 疾病預(yù)后因素研究設(shè)計在心臟瓣膜置換術(shù)后抗凝治療臨床研究中的應(yīng)用. 中國胸心血管外科臨床雜志, 2011, 18 (4):286-288.
- 7. 王家良, 王波, 主編. 臨床流行病學(xué):臨床科研設(shè)計, 測量與評價. 第3版. 上海:上??茖W(xué)技術(shù)出版社, 2009. 434-435.
- 8. 孫振球, 徐勇勇, 主編. 醫(yī)學(xué)衛(wèi)生統(tǒng)計. 第3版. 北京:人民衛(wèi)生出版社, 2010. 318.
- 9. Mcculloch WS, Pitts W. A logical calculus of the ideas immanent in nervous activity. Bull Math Biol, 1990, 52 (1â):99-115.
- 10. Minsky M, Papert S, Chief editor. Perceptron (expanded edition). Cambridge, MA:MIT Press, 1988. 1969.
- 11. Rumelhart D, Hintont GE, Williams RJ. Learning representations by back-propagating errors. Nature, 1986, 323 (9):533-536.
- 12. 施彥, 韓力群, 廉小親, 主編. 神經(jīng)網(wǎng)絡(luò)設(shè)計方法與實例分析. 北京:北京郵電大學(xué)出版社, 2009. 307-361.
- 13. Peng SY, Peng SK. Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks. Anaesthesia, 2008, 63 (7):705-713.
- 14. Akl A, Ismail AM, Ghoneim M. Prediction of graft survival of living-donor kidney transplantation:nomograms or artificial neural networks ? Transplantation, 2008, 86 (10):1401-1406.
- 15. Nilsson J, Ohlsson M, Thulin L, et al. Risk factor identification and mortality prediction in cardiac surgery using artificial neural networks. J Thorac Cardiovasc Surg, 2006, 132 (1):12-19.
- 16. Nashef S, Roques F, Hammill BG, et al. Validation of European system for cardiac operative risk evaluation (EuroSCORE)in North American cardiac surgery. Eur J Cardio-thoracic Surg, 2002, 22 (1):101-105.
- 17. Gogbashian A, Sedrakyan A, Treasure T. Euroscore:a systematic review of international performance. Euro J Cardio-thoracic Surg, 2004, 25 (5):695-700.
- 18. Yoshimura M, Takahashi Y, Uchida K, et al. Prediction of survival in prostate cancer patients by bone scan index using computer-assisted diagnosis system. Eur J Nucl Med Mol Imaging, 2011, 38 (Suppl 2):S414.
- 19. Scholl S, Biã¨che I, Pallud C, et al. Relevance of multiple biological parameters in breast cancer prognosis. Breast, 1996, 5 (1):21-30.
- 20. Ei MM, Akl A, Mosbah A, et al. Prediction of survival after radical cystectomy for invasive bladder carcinoma:risk group stratification, nomograms or artificial neural networks?J Urol, 2009, 182 (2):466-472.
- 21. 袁金秋, 劉雅莉, 楊克虎. 基于人工神經(jīng)網(wǎng)絡(luò)的數(shù)據(jù)挖掘技術(shù)在臨床中應(yīng)用進(jìn)展. 圖書與情報, 2010 (3):95-98.
- 22. 范炤, 呂吉元, 陳澤華, 等. 基于BP人工神經(jīng)網(wǎng)絡(luò)的急性前壁心肌梗塞冠脈內(nèi)支架術(shù)一年預(yù)后模型研究. 中國衛(wèi)生統(tǒng)計, 2010, 27 (1):71-73, 82.
- 23. 張鳴. 初步構(gòu)建基于我國肝移植受體的生存評估模型及其與MELD的比較研究. 成都:四川大學(xué), 2006. 1-87.
- 24. 蔡煜東, 官家文, 甘駿人, 等. 人工神經(jīng)網(wǎng)絡(luò)方法在乳腺癌死亡率研究中的應(yīng)用. 中國生物醫(yī)學(xué)工程學(xué)報, 1994, 13 (4):364-366.
- 25. 黃德生, 周寶森, 劉延齡, 等. BP人工神經(jīng)網(wǎng)絡(luò)用于肺鱗癌預(yù)后預(yù)測. 中國衛(wèi)生統(tǒng)計, 2000, 17 (6):337-340.
- 26. 姜成華, 王正國, 朱佩芳, 等. 基于神經(jīng)網(wǎng)絡(luò)的創(chuàng)傷預(yù)后仿真模型. 中華創(chuàng)傷雜志, 1997, 13 (3):42-44.
- 27. De Laurentiis M, De Placido S, Bianco AR, et al. A prognostic model that makes quantitative estimates of probability of relapse for breast cancer patients. Clin Cancer Res, 1999, 5 (12):4133-4139.
- 28. Piaggi P, Lippi C, Fierabracci P, et al. Artificial neural networks in the outcome prediction of adjustable gastric banding in obese women. PLoS One, 2010, 5 (10):e13624.
- 29. Tu JV, Guerriere MJ. Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Comput Biomed Res, 1993, 26 (3):220-229.
- 30. Lin E, Hwang Y, Wang SC, et al. An artificial neural network approach to the drug efficacy of interferon treatments. Pharmacogenomics, 2006, 7 (7):1017-1024.
- 31. Chang HH, Chen PS, Giacomini KM. A neural network model for predicting treatment response of antidepressant in patients with major depressive disorder. Biol Psychiatry, 2012, 71 (8):286S.
- 32. Solomon I, Maharshak N, Chechik G, et al. Applying an artificial neural network to warfarin maintenance dose prediction. Isr Med Assoc J, 2004, 6 (12):732-735.
- 33. Dipti I, Peter BS, Almassy RJ, et al. Artificial neural networks:Current status in cardiovascular medicine. J Am Coll Cardiol, 1996, 28 (2):515-521.