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Takayuki Takahashi,Hikaru Matsuoka,Rieko Sakurai,Jun Akatsuka,Yusuke Kobayashi,Masaru Nakamura,Takashi Iwata,Kouji Banno,Motomichi Matsuzaki,Jun Takayama,Daisuke Aoki,Yoichiro Yamamoto,Gen Tamiya 대한부인종양학회 2022 Journal of Gynecologic Oncology Vol.33 No.5
Objective: Human papillomavirus subtypes are predictive indicators of cervical intraepithelial neoplasia (CIN) progression. While colposcopy is also an essential part of cervical cancer prevention, its accuracy and reproducibility are limited because of subjective evaluation. This study aimed to develop an artificial intelligence (AI) algorithm that can accurately detect the optimal lesion associated with prognosis using colposcopic images of CIN2 patients by utilizing objective AI diagnosis. Methods: We identified colposcopic findings associated with the prognosis of patients with CIN2. We developed a convolutional neural network that can automatically detect the rate of high-grade lesions in the uterovaginal area in 12 segments. We finally evaluated the detection accuracy of our AI algorithm compared with the scores by multiple gynecologic oncologists. Results: High-grade lesion occupancy in the uterovaginal area detected by senior colposcopists was significantly correlated with the prognosis of patients with CIN2. The detection rate for high-grade lesions in 12 segments of the uterovaginal area by the AI system was 62.1% for recall, and the overall correct response rate was 89.7%. Moreover, the percentage of high-grade lesions detected by the AI system was significantly correlated with the rate detected by multiple gynecologic senior oncologists (r=0.61). Conclusion: Our novel AI algorithm can accurately determine high-grade lesions associated with prognosis on colposcopic images, and these results provide an insight into the additional utility of colposcopy for the management of patients with CIN2.
Tanaka, Hideyuki,Matsuoka, Yasutomo,Kawakami, Takuma,Azegami, Yasuhiko,Yamamoto, Masashi,Ohtake, Kazuo,Sone, Takayuki Council on Tall Building and Urban Habitat Korea 2019 International journal of high-rise buildings Vol.8 No.4
We performed calculations combining optimization technologies and Computational Fluid Dynamics (CFD) aimed at reducing wind forces and mitigating wind environments (local strong winds) around buildings. However, the Reynolds Averaged Navier-stokes Simulation (RANS), which seems somewhat inaccurate, needs to be used to create a realistic CFD optimization tool. Therefore, in this study we explored the possibilities of optimizing calculations using RANS. We were able to demonstrate that building configurations advantageous to wind forces could be predicted even with RANS. We also demonstrated that building layouts was more effective than building configurations in mitigating local strong winds around tall buildings. Additionally, we used the Convolutional Neural Network (CNN) as an airflow prediction method alternative to CFD in order to increase the speed of optimization calculations, and validated its prediction accuracy.
Risako Kakuta,Ryuichi Nakano,Hisakazu Yano,Daiki Ozawa,Nobuo Ohta,Takayuki Matsuoka,Naotaka Motoyoshi,Shunsuke Kawamoto,Yoshikatsu Saiki,Yukio Katori,Mitsuo Kaku 대한진단검사의학회 2020 Annals of Laboratory Medicine Vol.40 No.3
Dear Editor, Infected aortic aneurysm (IAA) is an uncommon, but life-threatening condition. Identification of the causative pathogen is essential for accurate diagnosis and effective treatment. However, 14–40% of IAA cases are culture-negative [1]. IAA due to Streptococcus pneumoniae is rare, and reports of the involvement of S. pneumoniae capsular serotypes and sequence types (STs) in IAA are even rarer [2-5]. We identified S. pneumoniae from culture-negative IAA by genetic analysis. To the best of our knowledge, as of 2019, only 59 cases of pneumococcal IAA have been reported in France, the United Kingdom (UK), the Netherlands, Germany, Switzerland, Belgium, Denmark, the United States (USA), Canada, Chile, Japan, Hong Kong, Korea, and Austria since 1977 [2-5]. In the previous cases of IAA due to S. pneumoniae, capsular serotype analysis was reported only for seven: 10A and 23F in the UK, 4 and 8 in Denmark, 19F in Hong Kong, 4 in Belgium, and 23 in USA [2-5]. We report the first two cases of culture-negative IAA due to non-vaccine S. pneumoniae serotype 23A, ST338. The study protocol was approved by the Institutional Ethics Committees of Tohoku University, Sendai, Japan (No. 2018-1-456).