This paper aims to explore the application of Internet of Things (IoT) in healthcare under the rapid development of artificial intelligence technology, systematically analyze the resulting iatrogenic risks, and examine their conceptualization, classification, and governance pathways. Through a systematic review of relevant literature and based on Bogner's classification of medical failures, this study categorizes iatrogenic risks into active and latent types and identifies risk factors in the medical application of IoT technology. The research finds that algorithm limitations and cybersecurity issues are the main factors contributing to active iatrogenic risks, while human-machine integration challenges and loose regulatory environments are the primary factors leading to latent iatrogenic risks. While IoT medical technology improves healthcare service efficiency and quality, it also introduces iatrogenic risks. The study indicates that precise efforts in technical security regulatory standards and multi-stakeholder risk avoidance mechanisms are necessary to establish an IoT healthcare risk control system and reduce iatrogenic risks.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |