Big Data and Data Science in Critical Care.
Abstrak
The digitalization of the health-care system has resulted in a deluge of clinical big data and has prompted the rapid growth of data science in medicine. Data science, which is the field of study dedicated to the principled extraction of knowledge from complex data, is particularly relevant in the critical care setting. The availability of large amounts of data in the ICU, the need for better evidence-based care, and the complexity of critical illness makes the use of data science techniques and data-driven research particularly appealing to intensivists. Despite the increasing number of studies and publications in the field, thus far there have been few examples of data science projects that have resulted in successful implementations of data-driven systems in the ICU. However, given the expected growth in the field, intensivists should be familiar with the opportunities and challenges of big data and data science. The present article reviews the definitions, types of algorithms, applications, challenges, and future of big data and data science in critical care.
Topik & Kata Kunci
Penulis (3)
MD L. Nelson Sanchez-Pinto
PhD Yuan Luo
MD Matthew M. Churpek
Akses Cepat
- Tahun Terbit
- 2018
- Bahasa
- en
- Total Sitasi
- 253×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1016/j.chest.2018.04.037
- Akses
- Open Access ✓