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Journal Abstract Search

69 related items for PubMed ID: 7934708

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  • 2. Use of an artificial neural network for the diagnosis of myocardial infarction.
    Baxt WG.
    Ann Intern Med; 1991 Dec 01; 115(11):843-8. PubMed ID: 1952470
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  • 4. Analysis of the clinical variables driving decision in an artificial neural network trained to identify the presence of myocardial infarction.
    Baxt WG.
    Ann Emerg Med; 1992 Dec 01; 21(12):1439-44. PubMed ID: 1443838
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  • 5. The added value of ECG-gating for the diagnosis of myocardial infarction using myocardial perfusion scintigraphy and artificial neural networks.
    Gjertsson P, Lomsky M, Richter J, Ohlsson M, Tout D, van Aswegen A, Underwood R, Edenbrandt L.
    Clin Physiol Funct Imaging; 2006 Sep 01; 26(5):301-4. PubMed ID: 16939508
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  • 8. Using patient-reportable clinical history factors to predict myocardial infarction.
    Wang SJ, Ohno-Machado L, Fraser HS, Kennedy RL.
    Comput Biol Med; 2001 Jan 01; 31(1):1-13. PubMed ID: 11058690
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  • 12. Advanced integrated technique in breast cancer thermography.
    Ng EY, Kee EC.
    J Med Eng Technol; 2008 Jan 01; 32(2):103-14. PubMed ID: 17852648
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  • 13. Neural networks and early diagnosis of myocardial infarction.
    Andreae MH.
    Lancet; 1996 Feb 10; 347(8998):407-8. PubMed ID: 8598741
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  • 14. Neural networks and early diagnosis of myocardial infarction.
    Kennedy RL, Burton AM, Harrison RF.
    Lancet; 1996 Feb 10; 347(8998):407. PubMed ID: 8598740
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  • 20. Use of an artificial neural network to predict head injury outcome.
    Rughani AI, Dumont TM, Lu Z, Bongard J, Horgan MA, Penar PL, Tranmer BI.
    J Neurosurg; 2010 Sep 10; 113(3):585-90. PubMed ID: 20020844
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