Second-Generation Sequencing with Deep Reinforcement Learning for Lung Infection Detection
| Autor: | Na Zhang, Junxiu Sheng, Liyan Yu, Hong Yuan, Gerui Zhang, Zhao Jingyuan, Zhuo Liu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Lung Diseases
Medicine (General) medicine.medical_specialty Article Subject Lung infection Big data Biomedical Engineering MEDLINE Health Informatics 02 engineering and technology 03 medical and health sciences Deep Learning R5-920 Health care Medical technology 0202 electrical engineering electronic engineering information engineering medicine Humans Reinforcement learning Medical physics Diagnosis Computer-Assisted Prospective Studies R855-855.5 030304 developmental biology 0303 health sciences business.industry Gene Expression Profiling Sequence Analysis DNA Identification (information) 020201 artificial intelligence & image processing Surgery business Internet of Things Research Article Biotechnology |
| Zdroj: | Journal of Healthcare Engineering, Vol 2020 (2020) Journal of Healthcare Engineering |
| ISSN: | 2040-2309 2040-2295 |
| Popis: | Recently, deep reinforcement learning, associated with medical big data generated and collected from medical Internet of Things, is prospective for computer-aided diagnosis and therapy. In this paper, we focus on the application value of the second-generation sequencing technology in the diagnosis and treatment of pulmonary infectious diseases with the aid of the deep reinforcement learning. Specifically, the rapid, comprehensive, and accurate identification of pathogens is a prerequisite for clinicians to choose timely and targeted treatment. Thus, in this work, we present representative deep reinforcement learning methods that are potential to identify pathogens for lung infection treatment. After that, current status of pathogenic diagnosis of pulmonary infectious diseases and their main characteristics are summarized. Furthermore, we analyze the common types of second-generation sequencing technology, which can be used to diagnose lung infection as well. Finally, we point out the challenges and possible future research directions in integrating deep reinforcement learning with second-generation sequencing technology to diagnose and treat lung infection, which is prospective to accelerate the evolution of smart healthcare with medical Internet of Things and big data. |
| Databáze: | OpenAIRE |
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