Go to contents
Go to menu
°Ë»ö¾î ÀÔ·Â
Ȩ
·Î±×ÀÎ
Áñ°Üã±âÃß°¡
ENGLlSH
°í±Þ°Ë»ö
Àú³Îº°°Ë»ö
¿ø¹®Á¦°ø Àú³Îº°°Ë»ö
¿¬±¸ºÐ¾ßº° °Ë»ö
ÇÐȸ/Çùȸ Á¤º¸
Àú³Î Á¤º¸
Àú³Î Åõ°í ±ÔÁ¤
KMbase ¼Ò°³
°øÁö»çÇ×
¾÷µ¥ÀÌÆ® Á¤º¸
³» Á¤º¸
ÀúÀå ³í¹®
°ü½ÉºÐ¾ß ³í¹®
°ü½ÉÇÐȸ/ÇмúÁ¤º¸
¿ø¹®½Åû
°ü½ÉºÐ¾ß °ü¸®
½ºÅ©¸³Æ® ȯ°æ¿¡¼ Áö¿øµË´Ï´Ù.
³í¹®°Ë»ö
°í±Þ°Ë»ö
Àú³Îº°°Ë»ö
¿ø¹®Á¦°ø Àú³Î°Ë»ö
¿¬±¸ºÐ¾ßº° °Ë»ö
SITE LINK
PubMed
Google Scholar
KoreaScience
KISTI
KoreaMed
RISS
MEDLIS
Cross Check
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
( Journal of the Korean Dental Association )
: °Ë»ö°á°ú :
5
  
°Ë»ö°á°ú¸ðµÎ¼±ÅÃ
1
ÀΰøÁö´É µö·¯´×ÀÇ ¿ª»ç¿Í ÇöȲ, ±×¸®°í ¹Ì·¡ ¹æÇâ
History, Current Status and Future Directions of Deep Learning
ÀÌ¿øÁø ( Yi Won-Jin )
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
2022³â 60±Ç 5È£ 299 ~ 314
2
ÀΰøÁö´ÉÀÇ ¹Ì·¡
Future perspectives of artificial intelligence
ȲÀçÁØ ( Hwang Jae-Joon )
Çã¹Î¼® ( Heo Min-Suk )
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
2022³â 60±Ç 5È£ 290 ~ 298
3
¿µ»óÄ¡ÀÇÇп¡¼ÀÇ ÀΰøÁö´É ±â¼ú µ¿Çâ
Trend of Artificial Intelligence technology in oral and maxillofacial radiology
ÇÑ»ó¼± ( Han Sang-Sun )
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
2022³â 60±Ç 5È£ 282 ~ 289
4
´ëÇѹα¹ Ä¡°úÀÇ·áÁ¾»çÀÚÀÇ Äڷγª19 : 2³â°£ °¨¿°¹ß»ý ÇöȲºÐ¼® ¹× Ä¡°ú°¨¿°°ü¸®Áöħ ÃÖ½ÅÁö°ß
COVID-19 among dental healthcare workers in the Republic of Korea : Two years report of accumulative
...
Çã¼®¸ð ( Heo Seok-Mo )
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
2022³â 60±Ç 5È£ 269 ~ 280
5
µðÁöÅÐ ¼Â¾÷ ¸ðÇü¿¡¼ Á¦ÀÛµÈ jig¸¦ ÀÌ¿ëÇÑ µÎ °¡Áö ºê¶óÄÏ °£Á¢ Á¢Âø ¹æ¹ýÀÇ Á¤È®¼º ºñ±³
Comparison of accuracy of two indirect bonding methods using a jig fabricated from digital setup mod
...
ÀÌÁ¾Çö ( Lee Jong-Hyeon )
ÃÖµ¿¼ø ( Choi Dong-Soon ), ÀåÀλê ( Jang In-San ), Â÷ºÀ±Ù ( Cha Bong-Kuen )
´ëÇÑÄ¡°úÀÇ»çÇùȸÁö
2022³â 60±Ç 5È£ 258 ~ 268