notice
The original language of this website is Japanese. This website will be translated in English using a private automatic translation service. Translation results are dependent on an automatic translation system. No responsibility whatsoever is taken concerning the results of using this translation service. Please make use of this translation service with the understanding that automatic translation does not provide 100% accuracy. Moreover, site search cannot be performed in English.
2018 Academic Encouragement Award (38nd Medical Informatics Union Conference)
Excellent Oral Performance Award
Transforming catheter ablation with real-time visualization of atrial fibrillation based on intracardiac ECG processing
Takashi Ashihara
Shiga Medical University Medical Information Department/Shiga Medical University Department of Cardiovascular Medicine
Comprehensive exploration of the relationship between oral hypoglycemic drug concomitant patterns and treatment outcomes using hospital information system data
Natsuo Suda
Kochi University School of Medicine, Advanced Medical Science Course
Extraction of patient symptom expressions and symptom-disease relationship recognition appearing in web documents using Multi-Column Convolutional Neural Networks
Seiya Wada
Medical Informatics, Osaka University Graduate School of Medicine
best poster award
Attempt to implement FHIR web services on SS-MIX
Eizo Kimura
National of Health Sciences
Attempt to recognize dental information from intraoral images using deep learning
Yoichi Maruyama
Nagasaki University Hospital Medical Information Department Dental Branch
Research Encouragement Award
Examination of adjustment parameter values and cutoff values in text vectorization - In the detection method of aspiration pneumonia using nursing observation records -
Shotaro Komaki
Kagoshima Medical Technology College
Study on the description method of analysis logic for analyzing electronic receipt information
Junpei Sato
of Industrial Science, University of Tokyo
Evaluation of finding concordance of renal pathological glomerular images for image diagnosis using AI
Ryohei Yamaguchi
Department of Medical Informatics, Graduate School of Medicine, The University of Tokyo
Attempt to predict the onset of nephrosis from time-series data of laboratory tests based on deep learning and interpret the prediction model