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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
¾ÏÀÇ ¿¹ÈÄ ¿¹ÃøÀ» À§ÇÑ ±×·¡ÇÁ ±â¹ÝÀÇ ÁØÁöµµ ÇнÀ ¹æ¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Graph-based Semi-Supervised Learning Method for Predicting Prognosis of Cancer |
ÀúÀÚ(Author) |
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Chihyun Park
Sanghyun Park
Hyunjin Kim
Yunku Yeu
Jaegyoon Ahn
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¿ø¹®¼ö·Ïó(Citation) |
VOL 19 NO. 02 PP. 0071 ~ 0076 (2013. 02) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®¿¡¼´Â ÁØÁöµµ ÇнÀ ¹æ¹ý¿¡ ±â¹ÝÇÏ¿© ´õ¿í Á¤È®ÇÏ°Ô ¾ÏÀÇ ¿¹Èĸ¦ ¿¹ÃøÇÒ ¼ö ÀÖ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ¹ýÀº À¯ÀüÀÚ ¹ßÇöÀ» ÃøÁ¤ÇÑ ¸¶ÀÌÅ©·Î¾î·¹ÀÌ µ¥ÀÌÅ͸¦ ±×·¡ÇÁ ±â¹ÝÀÇ ÁØÁöµµ ÇнÀ¿¡ Àû¿ëÇϱâ À§Çؼ »ùÇà ±â¹ÝÀÇ ±×·¡ÇÁ ¸ðµ¨ ±¸ÃàÇÏ´Â ´Ü°è¿Í ±¸ÃàµÈ ±×·¡ÇÁ ¸ðµ¨¿¡¼ ºñ¿ëÇÔ¼ö¸¦ ÀÌ¿ëÇÏ¿© ÃÖÁ¾ Ŭ·¡½º ·¹À̺íÀ» ¿¹ÃøÇÒ ¼ö ÀÖ´Â ºÎºÐÀ¸·Î ±¸¼ºµÇ¾î ÀÖ´Ù. Ŭ·¡½º ·¹À̺íÀÌ ¾ø´Â »ùÇõéÀÌ ¸¹Àº ¾Ï ¿¹ÈÄ °ü·Ã µ¥ÀÌÅÍ¿¡ ´ëÇؼ °á°úÀûÀ¸·Î ºñ±³ ¹æ¹ýº¸´Ù ¿ì¼öÇÑ ºÐ·ù Á¤È®µµ¸¦ º¸ÀÓÀ» È®ÀÎÇÏ¿´´Ù.
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¿µ¹®³»¿ë (English Abstract) |
In this paper, we propose a graph-based semi-supervised learning method for accurate prediction of cancer prognosis. Our method consist of two parts, one is about transforming mRNA microarray data into graph data structure for learning and the other is about predicting the class labels of unlabeled samples using cost function. As a result, we achieved that our method has outstanding accuracy compared to other methods in the prognosis related cancer data which have many unlabeled samples.
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Å°¿öµå(Keyword) |
ÁØÁöµµ ÇнÀ
¸¶ÀÌÅ©·Î¾î·¹ÀÌ
¾ÏÀÇ ¿¹ÈÄ ¿¹Ãø
Semi-Supervised Learning
Microarray
Prediction of Cancer Prognosis
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