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Review
. 2024 Dec 23:6:1502434.
doi: 10.3389/fdgth.2024.1502434. eCollection 2024.

Artificial intelligence in respiratory care

Affiliations
Review

Artificial intelligence in respiratory care

Manjush Karthika et al. Front Digit Health. .

Abstract

The evolution of artificial intelligence (AI) has revolutionised numerous aspects of our daily lives, with profound implications across various sectors, including healthcare. Although the concept of AI in healthcare was introduced in the early 1970s, the integration of this technology in healthcare is still in the evolution phase. Despite barriers, the current decade is witnessing an increased utility of AI into diverse specialities of the medical field to enhance precision medicine, predict diagnosis, therapeutic results, and prognosis; this includes respiratory medicine, critical care, and in their allied specialties. AI algorithms are widely studied in areas like mechanical ventilation, sleep medicine, lung ultrasound, and pulmonary function diagnostics and the results are found to be promising. The quality of patient care and safety can be greatly enhanced if respiratory care professionals fully understand the concept and importance of AI, as they are already incorporating various aspects of this technology into their clinical practice. Awareness of AI in the clinical field is essential during this phase; hence, it is desirable to establish widely accepted standards presented in a clear and accessible language. This article aims to describe the existing and prospective role of AI in the field of respiratory care and allied areas.

Keywords: artificial intelligence; deep learning; machine learning; mechanical ventilation; respiratory care.

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Conflict of interest statement

MS was employed by Chest Research & Training Pvt Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
An overview of artificial intelligence.
Figure 2
Figure 2
Machine learning versus deep learning.
Figure 3
Figure 3
Applications of artificial intelligence in respiratory care.

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