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dt-accepted=
dt-pub-year=2019
dt-pub=20190401
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kn-subject=
en-title=
kn-title=•½�¬30”N“x‰ªŽRˆãŠw‰ï�Ü‚ªŒˆ‚Ü‚é
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END

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cd-journal=joma
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kn-title=ˆê”Ê�à’c–@�l’ÃŽRŽœ•—‰ï ’ÃŽR’†‰›‹L”O•a
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END

start-ver=1.4
cd-journal=joma
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en-title=The 49th Okayama Rheumatology Conference
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start-ver=1.4
cd-journal=joma
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en-title=The 28th Annual Meeting of the Japanese Society of Pharmaceutical Health Care and Sciences
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en-aut-name=SendoToshiaki
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affil-num=1
en-affil=Department of Pharmacy, Okayama University Hospital
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start-ver=1.4
cd-journal=joma
no-vol=131
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kn-subject=
en-title=The 46th Japanese Society for Joint Diseases
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en-aut-name=OzakiToshifumi
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affil-num=1
en-affil=Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
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END

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cd-journal=joma
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kn-subject=
en-title=Tumor microenvironment affecting the effect of immuno-checkpoint inhibitors
kn-title=–Ɖuƒ`ƒFƒbƒNƒ|ƒCƒ“ƒg‘jŠQ–ò‚ÌŒø‰Ê‚ð�¶‰E‚·‚éŽîᇔ÷�¬ŠÂ‹«
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en-aut-name=NishiiKazuya 
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en-aut-name=Ohashi Kadoaki 
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en-aut-name=KiuraKatsuyuki 
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affil-num=1
en-affil=Department of Hematology, Oncology and Respiratory Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences 
kn-affil=‰ªŽR‘åŠw‘åŠw‰@ˆãŽ•–òŠw‘��‡Œ¤‹†‰È�@ŒŒ‰t�EŽîá‡�EŒÄ‹zŠí“à‰ÈŠw 

affil-num=2
en-affil=Department of Respiratory Medicine, Okayama University Hospital 
kn-affil=‰ªŽR‘åŠw•a‰@�@ŒÄ‹zŠí�EƒAƒŒƒ‹ƒM�[“à‰È 

affil-num=3
en-affil=Department of Respiratory Medicine, Okayama University Hospital
kn-affil=‰ªŽR‘åŠw•a‰@�@ŒÄ‹zŠí�EƒAƒŒƒ‹ƒM�[“à‰È 
END

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en-title=Drug interaction�i44. Combination with molecular target drugs in rheumatoid arthritis�j
kn-title=–ò•¨‘ŠŒÝ�ì—p�i44�\ŠÖ�߃ŠƒEƒ}ƒ`‚Ì•ªŽq•W“IŽ¡—Öò�j
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en-aut-name=MaruoAkinori
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en-aut-name=EsumiSatoru 
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en-aut-name=KitamuraYoshihisa
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en-aut-name=SendoToshiaki
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affil-num=1
en-affil=Department of Pharmacy, Okayama University Hospital 
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affil-num=2
en-affil=Department of Pharmacy, Okayama University Hospital
kn-affil=‰ªŽR‘åŠw•a‰@�@–ò�Ü•”

affil-num=3
en-affil=Department of Pharmacy, Okayama University Hospital 
kn-affil=‰ªŽR‘åŠw•a‰@�@–ò�Ü•”

affil-num=4
en-affil=Department of Pharmacy, Okayama University Hospital 
kn-affil=‰ªŽR‘åŠw•a‰@�@–ò�Ü•”
END

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cd-journal=joma
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dt-pub-year=2019
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en-title=‚p28�E‚p29�E‚p30
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kn-subtitle=
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END

start-ver=1.4
cd-journal=joma
no-vol=131
cd-vols=
no-issue=1
article-no=
start-page=41
end-page=43
dt-received=
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dt-accepted=
dt-pub-year=2019
dt-pub=20190401
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Our approach to cancer genomic medicine at Okayama University Hospital
kn-title=–{–M‚É‚¨‚¯‚邪‚ñƒQƒmƒ€ˆã—Â̓WŠJ‚Æ ‰ªŽR‘åŠw•a‰@‚Å‚ÌŽæ‚è‘g‚Ý
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=
en-copyright=
kn-copyright=

en-aut-name=ToyookaShinichi
en-aut-sei=Toyooka
en-aut-mei=Shinichi
kn-aut-name=–L‰ª�Lˆê 
kn-aut-sei=–L‰ª
kn-aut-mei=�Lˆê 
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ORCID=

en-aut-name=TomidaShuta
en-aut-sei=Tomida
en-aut-mei=Shuta
kn-aut-name=•y“c�G‘¾ 
kn-aut-sei=•y“c
kn-aut-mei=�G‘¾ 
aut-affil-num=2
ORCID=

affil-num=1
en-affil=General Thoracic Surgery, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
kn-affil=‰ªŽR‘åŠw‘åŠw‰@ˆãŽ•–òŠw‘��‡Œ¤‹†‰È�@ŒÄ‹zŠí�E“û‘B“à•ª”åŠO‰ÈŠw

affil-num=2
en-affil=Center for Comprehensive Genomic Medicine, Okayama University Hospital 
kn-affil=‰ªŽR‘åŠw•a‰@�@ƒQƒmƒ€ˆã—Ñ��‡ˆã—ÃZƒ“ƒ^�[
en-keyword= ‚ª‚ñƒQƒmƒ€ˆã—Ã
kn-keyword= ‚ª‚ñƒQƒmƒ€ˆã—Ã
en-keyword= ‰ªŽR‘åŠw•a‰@
kn-keyword= ‰ªŽR‘åŠw•a‰@
en-keyword=ƒvƒŒƒVƒWƒ‡ƒ“ƒ�ƒfƒBƒXƒ“
kn-keyword=ƒvƒŒƒVƒWƒ‡ƒ“ƒ�ƒfƒBƒXƒ“
END

start-ver=1.4
cd-journal=joma
no-vol=131
cd-vols=
no-issue=1
article-no=
start-page=35
end-page=39
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20190401
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=A Morgagni hernia repaired laparoscopically using Ventralight ST? mesh
kn-title=Ventralight ST?‚ð—p‚¢‚Ä• �o‹¾‰ºŽè�p‚Å�C•œ‚µ‚½ Morgagni �Eƒwƒ‹ƒjƒA‚Ì1—á
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=A 78-year-old Japanese woman was referred to our hospital because of fecal occult blood. Barium enema and CT colonography revealed the herniation of the transverse colon and the greater omentum into the right hemithorax through a retrosternal defect. We diagnosed a Morgagni hernia, and we performed a laparoscopic hernia repair with a three-port approach. The invaginated transverse colon and omentum were easily reduced into the abdominal cavity. The size of the hernial orifice was estimated to be approx. 2.5�~4 cm. We placed Ventralight ST? mesh over the hernial orifice without hernial sac resection, and we used the double-crown technique to fix the mesh with a hernia stapler. The postoperative course was uneventful, and the patient was discharged on the 5th postoperative day with no complications. There has been no recurrence at 2 years after the surgery. Laparoscopic repair is a safe, less-invasive and useful method for repairing a Morgagni hernia. 
en-copyright=
kn-copyright=

en-aut-name=Murakami Takayoshi 
en-aut-sei=Murakami 
en-aut-mei=Takayoshi 
kn-aut-name=‘º�ãŒh�Ë 
kn-aut-sei=‘º�ã
kn-aut-mei=Œh�Ë 
aut-affil-num=1
ORCID=

en-aut-name=Fujimoto Yoshimi 
en-aut-sei=Fujimoto 
en-aut-mei=Yoshimi 
kn-aut-name=“¡–{‘PŽO
kn-aut-sei=“¡–{
kn-aut-mei=‘PŽO
aut-affil-num=2
ORCID=

en-aut-name=Murashima Nobutaka 
en-aut-sei=Murashima 
en-aut-mei=Nobutaka 
kn-aut-name=‘º“ˆ�M�® 
kn-aut-sei=‘º“ˆ
kn-aut-mei=�M�® 
aut-affil-num=3
ORCID=

en-aut-name=NishinaTakuya 
en-aut-sei=Nishina
en-aut-mei=Takuya 
kn-aut-name=�m‰È‘ñ–ç
kn-aut-sei=�m‰È
kn-aut-mei=‘ñ–ç
aut-affil-num=4
ORCID=

en-aut-name=SugiuKumi
en-aut-sei=Sugiu
en-aut-mei=Kumi
kn-aut-name=�™�¶‹vŽÀ 
kn-aut-sei=�™�¶
kn-aut-mei=‹vŽÀ 
aut-affil-num=5
ORCID=

en-aut-name=MatsumotoTakamasa 
en-aut-sei=Matsumoto
en-aut-mei=Takamasa 
kn-aut-name=�¼–{�„�¹
kn-aut-sei=�¼–{
kn-aut-mei=�„�¹
aut-affil-num=6
ORCID=

affil-num=1
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È

affil-num=2
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È

affil-num=3
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È

affil-num=4
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È

affil-num=5
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È

affil-num=6
en-affil=Department of Surgery, Kurashiki Medical Center
kn-affil=‘q•~�¬�l•aƒZƒ“ƒ^�[�@ŠO‰È
en-keyword=Morgagni �Eƒwƒ‹ƒjƒA (Morgagni hernia)
kn-keyword=Morgagni �Eƒwƒ‹ƒjƒA (Morgagni hernia)
en-keyword=‹¹�œŒãƒwƒ‹ƒjƒA (retrosternal hernia)
kn-keyword=‹¹�œŒãƒwƒ‹ƒjƒA (retrosternal hernia)
en-keyword=• �o‹¾‰ºŽè�p (laparoscopic repair)
kn-keyword=• �o‹¾‰ºŽè�p (laparoscopic repair)
en-keyword=Ventralight ST?
kn-keyword=Ventralight ST?
END

start-ver=1.4
cd-journal=joma
no-vol=131
cd-vols=
no-issue=1
article-no=
start-page=29
end-page=34
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2019
dt-pub=20190401
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=Better diagnostic performance using computer-assisted diagnostic support systems in internal medicine
kn-title=“à‰È‚É‚¨‚¯‚éƒRƒ“ƒsƒ…�[ƒ^—˜—p�f’fŽx‰‡ƒVƒXƒeƒ€‚É‚æ‚é�f’f‰ü‘P
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=The recent application of artificial intelligence�iAI�jto clinical medicine has confirmed the usefulness of AI for diagnostic imaging, histopathological examinations, and dermatologic screening. Clinical decision support systems are another promising area to which AI could contribute toward better clinical decisions. We have developed computer-assisted diagnostic support systems to reduce human diagnostic errors such as delayed diagnoses, misdiagnoses, and overdiagnoses. Our three Diagnosis Reminder�iDR�jsystems include two AI systems that use machine learning in their diagnosis algorithms. Here, we compared the diagnostic accuracy of a DR-supported group with that of an unassisted physicians group, using three difficult patient cases provided by experts in general medicine.
�@Our analyses revealed that the three AI diagnostic systems could not provide accurate differential diagnoses up to top 10 in all three patient cases because of incomplete data inputs for machine learning. However, the first DR system, which was developed by an experienced diagnostician over the last 35 years, showed very useful performance in reducing human diagnostic errors when it was used by an expert physician. The use of AI diagnostic systems by knowledgeable physicians will lead to better diagnostic performance. We also discuss the current scenario, future challenges, and prospects for AI diagnostic systems herein. 
en-copyright=
kn-copyright=

en-aut-name=KuriyamaYutaka
en-aut-sei=Kuriyama
en-aut-mei=Yutaka
kn-aut-name=ŒIŽR—T
kn-aut-sei=ŒIŽR
kn-aut-mei=—T
aut-affil-num=1
ORCID=

en-aut-name=Sota Yumi
en-aut-sei=Sota 
en-aut-mei=Yumi
kn-aut-name=‘]“c—S–¯
kn-aut-sei=‘]“c
kn-aut-mei=—S–¯
aut-affil-num=2
ORCID=

en-aut-name=YanoAika
en-aut-sei=Yano
en-aut-mei=Aika
kn-aut-name=–î–숤‰Ø 
kn-aut-sei=–î–ì
kn-aut-mei=ˆ¤‰Ø 
aut-affil-num=3
ORCID=

en-aut-name=YasudaHideki
en-aut-sei=Yasuda
en-aut-mei=Hideki
kn-aut-name=ˆÀ“c‰pŒÈ
kn-aut-sei=ˆÀ“c
kn-aut-mei=‰pŒÈ
aut-affil-num=4
ORCID=

en-aut-name=IshiiOsamu
en-aut-sei=Ishii
en-aut-mei=Osamu
kn-aut-name=�Έä�C 
kn-aut-sei=�Έä
kn-aut-mei=�C 
aut-affil-num=5
ORCID=

en-aut-name=Saio Takeo
en-aut-sei=Saio 
en-aut-mei=Takeo
kn-aut-name=�Ä”ö•�˜Y
kn-aut-sei=�Ä”ö
kn-aut-mei=•�˜Y
aut-affil-num=6
ORCID=

en-aut-name=TorigoeKeijiro
en-aut-sei=Torigoe
en-aut-mei=Keijiro
kn-aut-name=’¹‰zŒbŽ¡˜Y
kn-aut-sei=’¹‰z
kn-aut-mei=ŒbŽ¡˜Y
aut-affil-num=7
ORCID=

en-aut-name=UedaTakeshi 
en-aut-sei=Ueda
en-aut-mei=Takeshi 
kn-aut-name=�ã“c�„Žm 
kn-aut-sei=�ã“c
kn-aut-mei=�„Žm 
aut-affil-num=8
ORCID=

en-aut-name=Shimizu Tarou 
en-aut-sei=Shimizu 
en-aut-mei=Tarou 
kn-aut-name=Žu�…‘¾˜Y
kn-aut-sei=Žu�…
kn-aut-mei=‘¾˜Y
aut-affil-num=9
ORCID=

en-aut-name=TokudaYasuharu
en-aut-sei=Tokuda
en-aut-mei=Yasuharu
kn-aut-name=“¿“cˆÀ�t
kn-aut-sei=“¿“c
kn-aut-mei=ˆÀ�t
aut-affil-num=10
ORCID=

affil-num=1
en-affil=Okayama University Medical School
kn-affil=‰ªŽR‘åŠwˆãŠw•”ˆãŠw‰È

affil-num=2
en-affil=Okayama University Medical School
kn-affil=‰ªŽR‘åŠwˆãŠw•”ˆãŠw‰È

affil-num=3
en-affil=Okayama University Medical School 
kn-affil=‰ªŽR‘åŠwˆãŠw•”ˆãŠw‰È

affil-num=4
en-affil=Yasuda Clinic of Internal Medicine
kn-affil=ˆã—Ö@�lˆÀ“c“à‰Èˆã‰@

affil-num=5
en-affil=Torigoe-iin
kn-affil=ˆã—Ö@�lŒb�^‰ï ’¹‰zˆã‰@

affil-num=6
en-affil=Health Management Office, SMBC Nikko Securities Inc
kn-affil=SMBC“ú‹»�ØŒ”�@Œ’�NŠÇ—�Žº

affil-num=7
en-affil=Torigoe-iin
kn-affil=ˆã—Ö@�lŒb�^‰ï ’¹‰zˆã‰@

affil-num=8
en-affil=Emergency and General Internal Medicine, Rakuwakai Marutamachi Hospital
kn-affil=—Œ˜a‰ïŠÛ‘¾’¬•a‰@�@‹~‹}‘��‡�f—ÉÈ

affil-num=9
en-affil=Department of Diagnostic and Generalist Medicine, Dokkyo Medical University
kn-affil=àÕ‹¦ˆã‰È‘åŠw�@‘��‡�f—ÈãŠw 

affil-num=10
en-affil=Muribushi Okinawa for Teaching Hospitals
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