The 24th International Symposium on Advanced Intelligent Systems (ISIS), Best Presentation Award,Interpretability of ESWL Outcome Prediction Model and Feature Selection Using SHAP valuesSoya Kobayashi Daisuke Fujita Syoji Kobashi
2023年12月
The 24th International Symposium on Advanced Intelligent Systems (ISIS), Best Presentation Award,Deep learning approach for early detection and prediction of chronic lung disease in neonates chest X-ray imagesRyunosuke Maeda Daisuke Fujita Syoji Kobashi
2023年12月
The 24th International Symposium on Advanced Intelligent Systems (ISIS), Best Application AwardNaoya Takashima Daisuke Fujita Syoji Kobashi
Fahmida Haque   Mamun B I Reaz   Muhammad E H Chowdhury   Mohd Ibrahim Bin Shapiai   Rayaz A Malik   Mohammed Alhatou   Syoji Kobashi   Iffat Ara   Sawal H M Ali   Ahmad A A Bakar   Mohammad Arif Sobhan Bhuiyan   
Diabetic sensorimotor polyneuropathy (DSPN) is a serious long-term complication of diabetes, which may lead to foot ulceration and amputation. Among the screening tools for DSPN, the Michigan neuropathy screening instrument (MNSI) is frequently de...
Lecture Notes in Networks and Systems 618 LNNS 243-254 2023年 [査読有り]
The number of heart disease cases as well as the death associated with it are rising in numbers every year. It is now more important than ever to diagnose heart abnormalities quickly and correctly to ensure proper treatment is provided in time. A ...
2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) 1-5 2022年11月
Self-removal problems, in which patients pull out their own medical tubing, remain unresolved while medical tubing introduces more than before. Not only patients can't receive proper treatment by removing of medical tubing, but also complications ...
2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) 1-3 2022年11月
Brain development in children between the ages of 0 and 3 is extremely rapid. In the diagnosis of the pediatric brain, quantitative methods for evaluating brain growth during this period are needed. We propose a method for predicting the developme...