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Digital Healthcare for Airway Diseases from Personal Environmental Exposure.
Park, Youngmok; Lee, Chanho; Jung, Ji Ye.
  • Park Y; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
  • Lee C; Severance Biomedical Science Institute, Yonsei Biomedical Research Institute, Yonsei University College of Medicine, Seoul, Korea.
  • Jung JY; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea. stopyes@yuhs.ac.
Yonsei Med J ; 63(Suppl): S1-S13, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1841296
ABSTRACT
Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies' abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Yonsei Med J Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Yonsei Med J Year: 2022 Document Type: Article