發(fā)布時間：2018-04-28 22:05

  本文選題：BP神經(jīng)網(wǎng)絡(luò) + 疾病預(yù)測��； 參考：《吉林大學(xué)》2012年碩士論文

【摘要】：隨著技術(shù)的進(jìn)步，計算機(jī)與其他領(lǐng)域的合作越來越密切，解決了很多其他領(lǐng)域以前無法解決的難題。與此同時，隨著生活水平和受教育程度的提高，健康問題越來越受到人們關(guān)注，將計算機(jī)應(yīng)用于醫(yī)療領(lǐng)域進(jìn)行疾病預(yù)測是當(dāng)前研究的熱點之一，并且意義重大。疾病的的預(yù)測有著越來越重要的意義，正逐漸受到人們關(guān)注。目前，對疾病預(yù)測的研究存在下面兩個問題。其一，在醫(yī)療方面，計算機(jī)等設(shè)備絕大多數(shù)還是被用于疾病的檢測而不是預(yù)測，此時計算機(jī)的作用僅僅是圖像處理，在顯示器上成像，甚至最終的結(jié)果還是需要醫(yī)生來人工進(jìn)行判斷。在疾病診斷上醫(yī)療設(shè)備、計算設(shè)備只是作為輔助工具發(fā)揮著檢測數(shù)據(jù)等最為基本的作用，醫(yī)生作為整個過程的核心不可或缺。其二，很多疾病發(fā)病前的征兆或者發(fā)病時的癥狀具有相似之處，由于專家所研究領(lǐng)域的不同，專家根據(jù)所掌握的知識以及個人的經(jīng)驗，再結(jié)合病人的其他癥狀，所得出來的診斷結(jié)果可能有所不同，這樣會造成嚴(yán)重的后果。 針對以上提出的問題，本文將BP神經(jīng)網(wǎng)絡(luò)應(yīng)用于心臟病預(yù)測,利用神經(jīng)系統(tǒng)的并行性，對心臟病進(jìn)行預(yù)測，降低預(yù)測的失效率，充分利用了這些疾病預(yù)測的相同數(shù)據(jù)部分，提高數(shù)據(jù)利用效率；預(yù)測結(jié)果具有節(jié)省時間，，并且可信度高的特征。是將計算機(jī)技術(shù)應(yīng)用于醫(yī)療領(lǐng)域的有效嘗試，計算機(jī)不在僅僅用于醫(yī)療上的檢測，更多的應(yīng)用于預(yù)測。同時，由于計算機(jī)的精確性，能夠盡量避免人為導(dǎo)致的誤差，提高預(yù)測的精確度。
[Abstract]:With the development of technology, the cooperation between computer and other fields is getting closer and closer. At the same time, with the improvement of living standard and education, people pay more and more attention to the health problem. It is one of the hotspots of current research to apply computer to disease prediction in medical field, and it is of great significance. The prediction of disease is becoming more and more important and people are paying more and more attention to it. At present, there are two problems in the study of disease prediction. First, in the medical field, the vast majority of devices such as computers are still used for disease detection rather than prediction. At this point, the role of computers is only to process images and to image them on the display. Even the final result requires a doctor to manually judge. In the medical equipment of disease diagnosis, the computing equipment only plays the most basic role such as testing data as an auxiliary tool, doctors as the core of the whole process is indispensable. Second, many diseases have similar symptoms before onset or symptoms at the time of onset. Because of the differences in the field of study by experts, experts combine other symptoms of patients according to their knowledge and personal experience. The resulting diagnosis may vary, with serious consequences. To solve the above problems, BP neural network is applied to heart disease prediction. Using the parallelism of nervous system, it can predict heart disease, reduce the failure rate of prediction, and make full use of the same data of these disease prediction. Improving the efficiency of data utilization, the prediction results have the characteristics of saving time and high reliability. It is an effective attempt to apply computer technology to medical field. Computer is not only used for medical detection, but also for prediction. At the same time, because of the accuracy of computer, it can avoid man-made errors and improve the accuracy of prediction.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：R318.0;TP183

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 鄧勇,施文康,朱振福;一種有效處理沖突證據(jù)的組合方法[J];紅外與毫米波學(xué)報;2004年01期

2 李萍;曾令可;稅安澤;金雪莉;劉艷春;王慧;;基于MATLAB的BP神經(jīng)網(wǎng)絡(luò)預(yù)測系統(tǒng)的設(shè)計[J];計算機(jī)應(yīng)用與軟件;2008年04期

3 徐從富;耿衛(wèi)東;潘云鶴;;Dempster-Shafer證據(jù)推理方法理論與應(yīng)用的綜述[J];模式識別與人工智能;1999年04期

4 關(guān)欣;衣曉;孫曉明;何友;;有效處理沖突證據(jù)的融合方法[J];清華大學(xué)學(xué)報(自然科學(xué)版)網(wǎng)絡(luò).預(yù)覽;2009年01期

5 王俊杰;陳景武;;BP神經(jīng)網(wǎng)絡(luò)在疾病預(yù)測中的應(yīng)用[J];數(shù)理醫(yī)藥學(xué)雜志;2008年03期

6 郭建全;趙偉;黃松嶺;;一種改進(jìn)的D-S證據(jù)合成規(guī)則[J];系統(tǒng)工程與電子技術(shù);2009年03期

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