메뉴 건너뛰기




Volumn 14, Issue 3, 2005, Pages 198-202

Predicting the type of pregnancy using artificial neural networks and multinomial logistic regression: A comparison study

Author keywords

Multinomial logistic regression; Neural networks; Prediction; Type of pregnancy

Indexed keywords


EID: 28844435445     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-004-0454-8     Document Type: Article
Times cited : (14)

References (56)
  • 1
    • 0002021523 scopus 로고
    • The uses and limits of linear models
    • Lindsey JK (1995) The uses and limits of linear models. Stat Comput 5:87-89
    • (1995) Stat Comput , vol.5 , pp. 87-89
    • Lindsey, J.K.1
  • 2
    • 1942422934 scopus 로고
    • Model uncertainty, data mining and statistical inference
    • Chatfield C (1995) Model uncertainty, data mining and statistical inference. J R Stat Soc 158:419-466
    • (1995) J R Stat Soc , vol.158 , pp. 419-466
    • Chatfield, C.1
  • 3
    • 0029038845 scopus 로고
    • The log transformation is special
    • Keene ON (1995) The log transformation is special. Stat Med 14:811-819
    • (1995) Stat Med , vol.14 , pp. 811-819
    • Keene, O.N.1
  • 4
    • 0032518739 scopus 로고    scopus 로고
    • Choosing among generalized linear models applied to medical data
    • Lindsey JK, Jones B (1998) Choosing among generalized linear models applied to medical data. Stat Med 17(1):59-68
    • (1998) Stat Med , vol.17 , Issue.1 , pp. 59-68
    • Lindsey, J.K.1    Jones, B.2
  • 8
    • 0030327681 scopus 로고    scopus 로고
    • Understanding neural networks as statistical tools
    • Warner B, Manavendra M (1996) Understanding neural networks as statistical tools. Am stat 50(4):284-293
    • (1996) Am Stat , vol.50 , Issue.4 , pp. 284-293
    • Warner, B.1    Manavendra, M.2
  • 15
    • 0032526110 scopus 로고    scopus 로고
    • Epidemiologic interpretation of artificial neural networks
    • Duh MS, Walker AM, Ayanian JZ (1998) Epidemiologic interpretation of artificial neural networks. Am J Epidemiol 147(2):1112-1122
    • (1998) Am J Epidemiol , vol.147 , Issue.2 , pp. 1112-1122
    • Duh, M.S.1    Walker, A.M.2    Ayanian, J.Z.3
  • 16
    • 0034159892 scopus 로고    scopus 로고
    • Prediction of coronary artery senosis by artificial networks
    • Mobley BA, Schecheer E, Moore WE (2000) Prediction of coronary artery senosis by artificial networks. Artif Intell Med 18:187-203
    • (2000) Artif Intell Med , vol.18 , pp. 187-203
    • Mobley, B.A.1    Schecheer, E.2    Moore, W.E.3
  • 17
    • 0034333656 scopus 로고    scopus 로고
    • Model selection for medical diagnostic dicision support system: Breast cancer detection case
    • West D, West V (2000) Model selection for medical diagnostic dicision support system: breast cancer detection case. Artif Intell Med 20:183-204
    • (2000) Artif Intell Med , vol.20 , pp. 183-204
    • West, D.1    West, V.2
  • 18
    • 0031921607 scopus 로고    scopus 로고
    • Feed forward neural networks for analysis of censored survival data: A practical logistic regression approach
    • Biganzoli E, Boracchi P, Mariani L et al (1998) Feed forward neural networks for analysis of censored survival data: a practical logistic regression approach. Stat Med 17(10):1169-1186
    • (1998) Stat Med , vol.17 , Issue.10 , pp. 1169-1186
    • Biganzoli, E.1    Boracchi, P.2    Mariani, L.3
  • 19
    • 0032520167 scopus 로고
    • Prediction and cross-validation of neural networks versus logistic regression: Using nepatic disorders as an example
    • Duh MS, Walker AM, Pagano M et al (1995) Prediction and cross-validation of neural networks versus logistic regression: using nepatic disorders as an example. Am J epidemiol 147(4):407-413
    • (1995) Am J Epidemiol , vol.147 , Issue.4 , pp. 407-413
    • Duh, M.S.1    Walker, A.M.2    Pagano, M.3
  • 20
    • 0034773012 scopus 로고    scopus 로고
    • A neural network approach to the outcome definition on first treatment with stertaline in a psychiatric population
    • Franchini L, Spagnolo C, Rossini D et al (2001) A neural network approach to the outcome definition on first treatment with stertaline in a psychiatric population. Artif Intell Med 23:239-248
    • (2001) Artif Intell Med , vol.23 , pp. 239-248
    • Franchini, L.1    Spagnolo, C.2    Rossini, D.3
  • 21
    • 0033240929 scopus 로고    scopus 로고
    • A comparison of Cox regression and neural networks for risk stratification in cases of acute lymphoblastic leukaemia in children
    • Groves DJ, Smye SW, Kinsey SE et al (1999) A comparison of Cox regression and neural networks for risk stratification in cases of acute lymphoblastic leukaemia in children. Neural Comput Appl 8:257-264
    • (1999) Neural Comput Appl , vol.8 , pp. 257-264
    • Groves, D.J.1    Smye, S.W.2    Kinsey, S.E.3
  • 23
    • 0030297904 scopus 로고    scopus 로고
    • Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes
    • Tu JV (1996) Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J Clin Epidemiol 49(11):1225-1231
    • (1996) J Clin Epidemiol , vol.49 , Issue.11 , pp. 1225-1231
    • Tu, J.V.1
  • 24
    • 0032931335 scopus 로고    scopus 로고
    • Internal representation in neural networks used for classification of anesthetic states and dosage
    • Vefghi L, Linkens DA (1999) Internal representation in neural networks used for classification of anesthetic states and dosage. Comput Methods Programs Biomed 59:75-89
    • (1999) Comput Methods Programs Biomed , vol.59 , pp. 75-89
    • Vefghi, L.1    Linkens, D.A.2
  • 25
    • 0033623037 scopus 로고    scopus 로고
    • Application of neural networks and sensivitivity analysis to improved prediction of trauma survival
    • Hunter A, Kennedy L, Henry J et al (2000) Application of neural networks and sensivitivity analysis to improved prediction of trauma survival. Comput Methods Programs Biomed 62:11-19
    • (2000) Comput Methods Programs Biomed , vol.62 , pp. 11-19
    • Hunter, A.1    Kennedy, L.2    Henry, J.3
  • 26
    • 0030848289 scopus 로고    scopus 로고
    • Neural network and linear regression models in residency selection
    • Pilon S, Tadberg D (1997) Neural network and linear regression models in residency selection. Am J Emerg Med 15(4):361-364
    • (1997) Am J Emerg Med , vol.15 , Issue.4 , pp. 361-364
    • Pilon, S.1    Tadberg, D.2
  • 27
    • 0030951433 scopus 로고    scopus 로고
    • Comparison of a genetic algorithm neural network with logistic regression for predicting outcome after surgery for patients with nonsmall cell lung carcinoma
    • Jefferson MF, Horan MA, Lucas SB et al (1997) Comparison of a genetic algorithm neural network with logistic regression for predicting outcome after surgery for patients with nonsmall cell lung carcinoma. Cancer 79:1338-1342
    • (1997) Cancer , vol.79 , pp. 1338-1342
    • Jefferson, M.F.1    Ma, H.2    Lucas, S.B.3
  • 28
    • 0028871535 scopus 로고
    • Prediction of rib fracture injury outcome by an artificial neural network
    • Dombi GW, Nadi P, Saxe JM et al (1995) Prediction of rib fracture injury outcome by an artificial neural network. J Trauma 39:915-921
    • (1995) J Trauma , vol.39 , pp. 915-921
    • Dombi, G.W.1    Nadi, P.2    Saxe, J.M.3
  • 29
    • 0030763240 scopus 로고    scopus 로고
    • The application of neural networks in predicting the outcome of in-vitro fertilization
    • Kufmann SJ, Eastaugh JL, Snowden S et al (1997) The application of neural networks in predicting the outcome of in-vitro fertilization. Hum Reprod 12(7):1454-1457
    • (1997) Hum Reprod , vol.12 , Issue.7 , pp. 1454-1457
    • Kufmann, S.J.1    Eastaugh, J.L.2    Snowden, S.3
  • 30
    • 0030061822 scopus 로고    scopus 로고
    • Prospective validation of artificial neural networks trained to identify acute myocardial infarction
    • Baxt WG, Skora J (1996) Prospective validation of artificial neural networks trained to identify acute myocardial infarction. Lancet 347:12-15
    • (1996) Lancet , vol.347 , pp. 12-15
    • Baxt, W.G.1    Skora, J.2
  • 31
    • 0034019922 scopus 로고    scopus 로고
    • A hierarchical neural network algorithm for robust and automatic windowing of MR images
    • Lai SH, Ming F (2000) A hierarchical neural network algorithm for robust and automatic windowing of MR images. Artif Intell Med 19:97-119
    • (2000) Artif Intell Med , vol.19 , pp. 97-119
    • Lai, S.H.1    Ming, F.2
  • 32
    • 0034776764 scopus 로고    scopus 로고
    • A sequential neural network. Model for diabetes prediction
    • Park J, Edington DW (2001) A sequential neural network. Model for diabetes prediction. Artif Intell Med 23:277-293
    • (2001) Artif Intell Med , vol.23 , pp. 277-293
    • Park, J.1    Edington, D.W.2
  • 33
    • 0031281245 scopus 로고    scopus 로고
    • Application of autonomous neural network systems to medical pattern classification tasus
    • Lim CP, Harrison RF, Kennedy RL (1997) Application of autonomous neural network systems to medical pattern classification tasus. Artif Intell Med 11:215-239
    • (1997) Artif Intell Med , vol.11 , pp. 215-239
    • Lim, C.P.1    Harrison, R.F.2    Kennedy, R.L.3
  • 34
    • 0034333688 scopus 로고    scopus 로고
    • A comparison between two neural network rule extraction techniques for the diagnostic of hepatobiliary disorder
    • Hayashi Y, Setono R, Yoshida K (2000) A comparison between two neural network rule extraction techniques for the diagnostic of hepatobiliary disorder. Artif Intell Med 20:205-216
    • (2000) Artif Intell Med , vol.20 , pp. 205-216
    • Hayashi, Y.1    Setono, R.2    Yoshida, K.3
  • 35
    • 0032033309 scopus 로고    scopus 로고
    • Neural networks for recognizing patterns in cardiotocograms
    • Ulbricht C, Dorffner G, Andreas L (1998) Neural networks for recognizing patterns in cardiotocograms. Artif Intell Med 12(3):271-284
    • (1998) Artif Intell Med , vol.12 , Issue.3 , pp. 271-284
    • Ulbricht, C.1    Dorffner, G.2    Andreas, L.3
  • 36
    • 18544399463 scopus 로고    scopus 로고
    • Evolving artificial neural networks for screening features from mammograms
    • Fogel DB, Wasson III EC, Boughton EM et al (1998) Evolving artificial neural networks for screening features from mammograms. Artif Intell Med 14(3):317-326
    • (1998) Artif Intell Med , vol.14 , Issue.3 , pp. 317-326
    • Fogel, D.B.1    Wasson III, E.C.2    Boughton, E.M.3
  • 37
    • 0028855843 scopus 로고
    • A neural network model for survival data
    • Faraggi D, Simon D (1995) A neural network model for survival data. Stat Med 14:73-81
    • (1995) Stat Med , vol.14 , pp. 73-81
    • Faraggi, D.1    Simon, D.2
  • 38
    • 0033105476 scopus 로고    scopus 로고
    • A neural network approach to the diagnosis of morbidity outcomes in trauma care
    • Marble RP, Healy JC (1999) A neural network approach to the diagnosis of morbidity outcomes in trauma care. Artif Intell Med 15:299-307
    • (1999) Artif Intell Med , vol.15 , pp. 299-307
    • Marble, R.P.1    Healy, J.C.2
  • 39
    • 0028328448 scopus 로고
    • A technique for using neural network analysis to perform survival analysis of censored data
    • De Laurentiis M, Ravdin PM (1994) A technique for using neural network analysis to perform survival analysis of censored data. Cancer Lett 77:127-138
    • (1994) Cancer Lett , vol.77 , pp. 127-138
    • De Laurentiis, M.1    Ravdin, P.M.2
  • 40
    • 0030219072 scopus 로고    scopus 로고
    • Application of the fuzzy ARTMAP neural network model to medical pattern classification
    • Dows J, Harrison RF, Kennedy RL et al (1996) Application of the fuzzy ARTMAP neural network model to medical pattern classification. Artif Intell Med 8:403-428
    • (1996) Artif Intell Med , vol.8 , pp. 403-428
    • Dows, J.1    Harrison, R.F.2    Kennedy, R.L.3
  • 41
    • 0028211443 scopus 로고
    • Computer-assisted cervical cancer screening using neural networks
    • Mango LJ (1994) Computer-assisted cervical cancer screening using neural networks. Cancer Lett 77:155-162
    • (1994) Cancer Lett , vol.77 , pp. 155-162
    • Mango, L.J.1
  • 42
    • 0030944929 scopus 로고    scopus 로고
    • Predicting breast cancer invasion with artificial neural networks on the basis of mammographie features
    • Lo JY (1997) Predicting breast cancer invasion with artificial neural networks on the basis of mammographie features. Radiology 203:159-163
    • (1997) Radiology , vol.203 , pp. 159-163
    • Lo, J.Y.1
  • 43
    • 0028342538 scopus 로고
    • Artificial neural network for the electrocardiographic diagnosis of heald myocardinal infarction
    • Heden B, Edenbrandt L, Haisty WK et al (1994) Artificial neural network for the electrocardiographic diagnosis of heald myocardinal infarction. Am J Cardiol 74:5-8
    • (1994) Am J Cardiol , vol.74 , pp. 5-8
    • Heden, B.1    Edenbrandt, L.2    Haisty, W.K.3
  • 44
    • 0034728368 scopus 로고    scopus 로고
    • On the misuse of artificial neural networks for prognostic and diagnostic classification in oncology
    • Scnwarzer G, Vach W, Schumacher M (2000) On the misuse of artificial neural networks for prognostic and diagnostic classification in oncology. Stat Med 19:541-561
    • (2000) Stat Med , vol.19 , pp. 541-561
    • Scnwarzer, G.1    Vach, W.2    Schumacher, M.3
  • 45
    • 28844489084 scopus 로고    scopus 로고
    • Influencing factors on unwanted pregnancy in Tehran
    • Iranian Medical
    • Khalaj-Abadi Farahani F, Sadat Hashemi SM (2002) Influencing factors on unwanted pregnancy in Tehran. (Iranian Medical) J Hakim 5(3):15-23
    • (2002) J Hakim , vol.5 , Issue.3 , pp. 15-23
    • Khalaj-Abadi Farahani, F.1    Sadat Hashemi, S.M.2
  • 47
    • 0032648867 scopus 로고    scopus 로고
    • Comparing neural networks approximation for different functional forms
    • Morgan P, Curry B, Beynon M (1999) Comparing neural networks approximation for different functional forms. Expert Syst 16(2):60-71
    • (1999) Expert Syst , vol.16 , Issue.2 , pp. 60-71
    • Morgan, P.1    Curry, B.2    Beynon, M.3
  • 48
    • 0024880831 scopus 로고
    • Multi-layer feed forward networks are universal approximators
    • Hornik K, Stinchcombe M, White (1989) Multi-layer feed forward networks are universal approximators. Neural Netw 2(5):359-366
    • (1989) Neural Netw , vol.2 , Issue.5 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White3
  • 49
    • 21744442261 scopus 로고    scopus 로고
    • Layered neural networks as universal approximators
    • Cica I, Ware JA (1997) Layered neural networks as universal approximators. Lect Notes Comput Sci 1226:411-415
    • (1997) Lect Notes Comput Sci , vol.1226 , pp. 411-415
    • Cica, I.1    Ware, J.A.2
  • 51
    • 0026794310 scopus 로고
    • A goodness-of-fit approach to inference procedure for kappa statistic: Confidence interval construction, significance-testing and sample size estimation
    • Donner A, Eliasziwi M (1992) A goodness-of-fit approach to inference procedure for kappa statistic: confidence interval construction, significance-testing and sample size estimation. Stat Med 11:1511-1519
    • (1992) Stat Med , vol.11 , pp. 1511-1519
    • Donner, A.1    Eliasziwi, M.2
  • 52
    • 0033233944 scopus 로고    scopus 로고
    • A glossary of basic neural network terminology for regression problems
    • Stegemann JA,Buenfeld NR (1999) A glossary of basic neural network terminology for regression problems. Neural Comput Appl 8:290-296
    • (1999) Neural Comput Appl , vol.8 , pp. 290-296
    • Stegemann, J.A.1    Buenfeld, N.R.2
  • 54
    • 78651241597 scopus 로고    scopus 로고
    • The application of non-parametric techniques to solve classification problems in complex data sets in veterinary epidemiology: An example
    • Stark KDC, Pfeiffer DU (1999) The application of non-parametric techniques to solve classification problems in complex data sets in veterinary epidemiology: an example. Intell Data Anal 23-35
    • (1999) Intell Data Anal , pp. 23-35
    • Stark, K.D.C.1    Pfeiffer, D.U.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.