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Titlebook: Digital Health Transformation, Smart Ageing, and Managing Disability; 20th International C Kim Jongbae,Mounir Mokhtari,Lee Seungbok Confere

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樓主: 母牛膽小鬼
41#
發(fā)表于 2025-3-28 16:30:34 | 只看該作者
Conference proceedings‘‘‘‘‘‘‘‘ 2023elected from 41 submissions. They were organized in topical sections as follows:?IoT and AI Solutions for E-health,?Biomedical and Health Informatics,?Wellbeing Technologies,?Short Contributions: Medical Systems and E-health Solutions and?Short Contributions: Wellbeing Technologies..
42#
發(fā)表于 2025-3-28 20:08:37 | 只看該作者
43#
發(fā)表于 2025-3-29 00:59:19 | 只看該作者
The Internalization of Accountabilityation for further upcoming releases of additional and more advanced AI models and supporting pipelines (such as for ALS and MS progression prediction, patient stratification, and ambiental exposure modelling) in the following development.
44#
發(fā)表于 2025-3-29 03:14:33 | 只看該作者
Restructuring the Welfare State to manage chronic medical conditions. This article presents the implementation and test of a system preventing hip fractures resulting from falls using a fall detection and prediction system designed to protect and alert individuals during falls.
45#
發(fā)表于 2025-3-29 09:25:44 | 只看該作者
46#
發(fā)表于 2025-3-29 11:35:14 | 只看該作者
Detecting the?Pre-impact of?Falls in?the?Elderly, Along with?the?Use of?an?Airbag Belt for?Protectio to manage chronic medical conditions. This article presents the implementation and test of a system preventing hip fractures resulting from falls using a fall detection and prediction system designed to protect and alert individuals during falls.
47#
發(fā)表于 2025-3-29 17:15:02 | 只看該作者
48#
發(fā)表于 2025-3-29 22:24:59 | 只看該作者
0302-9743 tions as follows:?IoT and AI Solutions for E-health,?Biomedical and Health Informatics,?Wellbeing Technologies,?Short Contributions: Medical Systems and E-health Solutions and?Short Contributions: Wellbeing Technologies..978-3-031-43949-0978-3-031-43950-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
49#
發(fā)表于 2025-3-30 01:54:08 | 只看該作者
50#
發(fā)表于 2025-3-30 06:40:22 | 只看該作者
Deriving Physiological Information from?PET Images Using Machine Learninghy subjects, and were used to train four tree-based regression models. The predicted and reference values were compared by Bland-Altman analysis and regression model’s performance was evaluated by the mean absolute error (MAE). The best result was obtained by the XGBoost model with a MAE of 2.6. Bla
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