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Titlebook: Innovation in Medicine and Healthcare; Proceedings of 8th K Yen-Wei Chen,Satoshi Tanaka,Lakhmi C. Jain Conference proceedings 2020 The Edit

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樓主: 有靈感
31#
發(fā)表于 2025-3-26 23:53:05 | 只看該作者
Trial Run of a Patient Call System Using Mobile Devicese stress the outpatients undergo when waiting to be called for their examinations. After registering the patients at the reception desk, the patient call system will notify the outpatient prior to their examination by a sound played on their smartphones. To evaluate the effectiveness of our proposed
32#
發(fā)表于 2025-3-27 03:10:12 | 只看該作者
33#
發(fā)表于 2025-3-27 08:37:34 | 只看該作者
Improving Depth Perception using Multiple Iso-Surfaces for Transparent Stereoscopic Visualization of of the internal human body. Visualizing these data helps us to understand the complicated internal structure of the human body. Transparent stereoscopic visualization using depth information is a good way to visualize internal body structure. However, the position and depth information often become
34#
發(fā)表于 2025-3-27 12:41:23 | 只看該作者
Design and Simulation of a Robotic Manipulator for Laparoscopic Uterine Surgeries substitute the assistant doctor who handles the uterine positioner on command of the main surgeon. In the proposed setup, the main surgeon can control the positioner at the patient’s bedside via intuitive gestures through the LEAP. Motion Controller (LMC) allowing sterile and touchless operation. A
35#
發(fā)表于 2025-3-27 14:00:38 | 只看該作者
Self-Skill Training System for Chest Compressions in Neonatal Resuscitation Workshopred that objective reviews and self-training in basic skills workshops are effective. However, instructors are essential for current training, so it is difficult to do self-training. Even if there is an instructor, subjective evaluation and oral instructions are mainstream. In this study, we focused
36#
發(fā)表于 2025-3-27 20:56:40 | 只看該作者
37#
發(fā)表于 2025-3-27 23:17:21 | 只看該作者
38#
發(fā)表于 2025-3-28 02:17:26 | 只看該作者
39#
發(fā)表于 2025-3-28 07:45:41 | 只看該作者
Dynamic Facial Features in Positive-Emotional Speech for Identification of Depressive Tendenciesdents helps to reduce the number and intensity of their depressive episodes. Automatic prediction of depression from visual clues has gained increasing interest in recent years. This study proposes a deep learning model for depressive tendencies prediction, which extracts and fuses the dynamic facia
40#
發(fā)表于 2025-3-28 13:25:31 | 只看該作者
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