Waste of neural networks?
Magnavita, N.
Giornale Italiano di Medicina del Lavoro Ed Ergonomia 22(2): 207-208
2000
ISSN/ISBN: 1592-7830 PMID: 10911569 Document Number: 516666
Document emailed within 1 workday
Related Documents
Tenhagen, A.; Feuring, T.; Lippe, W.M. 1998: Testing the identity of hashish samples with ICP-AES and NAA and data handling with neural networks. 2. Data verification with the use of artificial neural networks Die Pharmazie 53(1): 39-42Signorini, D.F.; Slattery, J.M. 1995: Neural networks Lancet 346(8988): 1500
Oliver, R.M.; MacGregor, R.J.; Leffingwell, D.A. 1972: Electronic model for neural networks Biomedical Sciences Instrumentation 9: 109-113
Agatonovic-Kustrin, S.; Evans, A.; Alany, R.G. 2003: Prediction of corneal permeability using artificial neural networks Die Pharmazie 58(10): 725-729
Andreae, M.H. 1996: Neural networks and early diagnosis of myocardial infarction Lancet 347(8998): 407-408
Cicchetti, D.V. 1992: Neural networks and diagnosis in the clinical laboratory: state of the art Clinical Chemistry 38(1): 9-10
Hashemi, A.; Arabalibeik, H.; Agin, K. 2012: Classification of wheeze sounds using cepstral analysis and neural networks Studies in Health Technology and Informatics 173: 161-165
Maestú, F.; Quesney-Molina, F.; Ortiz-Alonso, T.; Campo, P.; Fernández-Lucas, A.; Amo, C. 2003: Cognition and neural networks, a new perspective based on functional neuroimaging Revista de Neurologia 37(10): 962-966
Liu, J.; Cai, Z. 1999: High order multi-layer neural networks and EEG diagnosing Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 16(4): 477-478; 496
Iasnitskiĭ, L.N.; Dumler, A.A.; Bogdanov, K.V.; Poleshchuk, A.N.; Cherepanov, F.M.; Makurina, T.V.; Chugaĭnov, S.V. 2013: Diagnosis and prognosis of cardiovascular diseases on the basis of neural networks Meditsinskaia Tekhnika 3: 42-44
Elaveyini, U.; Devi, S.P.; Rao, K.S. 2011: Neural networks prediction of preterm delivery with first trimester bleeding Archives of Gynecology and Obstetrics 283(5): 971-979
Schweiger, C.R.; Soeregi, G.; Spitzauer, S.; Maenner, G.; Pohl, A.L. 1993: Evaluation of laboratory data by conventional statistics and by three types of neural networks Clinical Chemistry 39(9): 1966-1971
Romeo, M.; Burden, F.; Quinn, M.; Wood, B.; McNaughton, D. 1998: Infrared microspectroscopy and artificial neural networks in the diagnosis of cervical cancer Cellular and Molecular Biology 44(1): 179-187
Slabbinck, B.; Dawyndt, P.; De Baets, B.; De Vos, P. 2006: Fame-based Bacillus species identification using artificial neural networks Communications in Agricultural and Applied Biological Sciences 71(1): 259-262
Mei, J.; Zhao, S.; Jin, F.; Zhang, L.; Liu, H.; Li, X.; Xie, G.; Li, X.; Xu, M. 2017: Deep Diabetologist: Learning to Prescribe Hypoglycemic Medications with Recurrent Neural Networks Studies in Health Technology and Informatics 245: 1277
Porter, C.R.; Crawford, E.D. 2003: Combining artificial neural networks and transrectal ultrasound in the diagnosis of prostate cancer Oncology 17(10): 1395-1399; Discussion 1399: 1403-1406
Festag, S.; Spreckelsen, C. 2017: Word Sense Disambiguation of Medical Terms via Recurrent Convolutional Neural Networks Studies in Health Technology and Informatics 236: 8-15
Li, Q.; Zhou, D. 2012: EEG-fMRi studies on the neural networks of the generalized spike and wave discharges: an overview Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 29(1): 179-183
Matheussen, B.V.; Thorolfsson, S.T. 2003: Estimation of snow covered area for an urban catchment using image processing and neural networks Water Science and Technology: a Journal of the International Association on Water Pollution Research 48(9): 155-164
Ayala, M.; Adjouadi, M.; Yaylali, I.; Jayakar, P. 2004: An optimization approach to recognition of epileptogenic data using neural networks with simplified input layers Biomedical Sciences Instrumentation 40: 181-186