医学
医疗保健
可穿戴计算机
临床决策支持系统
病历
健康档案
梅德林
医疗急救
可穿戴技术
医学教育
决策支持系统
人工智能
计算机科学
放射科
法学
经济
政治学
嵌入式系统
经济增长
作者
Paul Schoenhagen,Neil Mehta
标识
DOI:10.1093/eurheartj/ehw217
摘要
This editorial refers to ‘Machine learning for prediction of all-cause mortality in patient with suspected coronary artery disease: a 5-year multicentre prospective registry analysis’, by M. Motwani et al ., doi:10.1093/eurheartj/ehw188
Decision-making in medicine is based on the factual knowledge of the physician/practitioner, but is significantly influenced by various humanistic factors that play a role in the physician–patient relationship. Despite the increasing amount of electronic data available ‘online’ during the patient encounter, the ability to utilize a patient-centred approach is a central quality of superior practitioners. However, electronic health records (EHRs) and use of smart computer systems are having an increasing impact on established approaches in medicine.
The basic EHR collects and stores all data generated in a healthcare system (e.g. clinical notes, test results, and imaging studies). In addition to these data traditionally generated within the clinical setting, there are several novel feeds of information that can impact patient care. Specifically, wearable devices, and information from sensors and apps that capture and track various environmental, socio-economic, and other personal data can be valuable in understanding an individual's health status …
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