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您的检索式：作者名="Ryota Moriyama"
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| 1 | Influence of Moisture on BCN(low-K)Film for Interconnection Reliability显示文摘 | Hidemitsu Aoki Daisuke Watanabe Ryota Moriyama | 2008 | Diamond and Related Materials2008，17，45： | 1 |
| 2 | Artificial intelligence and machine learning could support drug development for hepatitis A virus internal ribosomal entry sites显示文摘Hepatitis A virus(HAV)infection is still an important health issue worldwide.Although several effective HAV vaccines are available,it is difficult to perform universal vaccination in certain countries.Therefore,it may be better to develop antivirals against HAV for the prevention of severe hepatitis A.We found that several drugs potentially inhibit HAV internal ribosomal entry site-dependent translation and HAV replication.Artificial intelligence and machine learning could also support screening of anti-HAV drugs,using drug repositioning and drug rescue approaches. | Tatsuo Kanda Reina Sasaki Ryota Masuzaki Mitsuhiko Moriyama | 2021 | Artificial Intelligence in Gastroenterology2021，2，1： | 0 |
| 3 | Application of artificial intelligence in hepatology:Minireview显示文摘With the rapid advancements in computer science,artificial intelligence(AI)has become an intrinsic part of our daily life and clinical practices.The concepts of AI,such as machine learning,deep learning,and big data,are extensively used in clinical and basic research.In this review,we searched for the articles in PubMed and summarized recent developments of AI concerning hepatology while focusing on the diagnosis and risk assessment of liver diseases.Ultrasound is widely conducted for the routine surveillance of hepatocellular carcinoma along with tumor markers.Computer-aided diagnosis is useful in the detection of tumors and characterization of space-occupying lesions.The prognosis of hepatocellular carcinoma can be estimated via AI using large-scale and highquality training datasets.The prevalence of nonalcoholic fatty liver disease is increasing worldwide and pivotal concern in the field is who will progress and develop hepatocellular carcinoma.Most AI studies require a large dataset,including laboratory or radiological findings and outcome data.AI will be useful in reducing medical errors,supporting clinical decisions,and predicting clinical outcomes.Thus,cooperation between AI and humans is expected to improve healthcare. | Ryota Masuzaki Tatsuo Kanda Reina Sasaki Naoki Matsumoto Kazushige Nirei Masahiro Ogawa Mitsuhiko Moriyama | 2020 | Artificial Intelligence in Gastroenterology2020，1，1： | 0 |
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