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Current Respiratory Medicine Reviews

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ISSN (Print): 1573-398X
ISSN (Online): 1875-6387

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Review Article

The Future of Cystic Fibrosis Care: Exploring AI's Impact on Detection and Therapy

Author(s): Biswajit Basu, Srabona Dutta, Monosiz Rahaman, Anirbandeep Bose, Sourav Das, Jigna Prajapati* and Bhupendra Prajapati*

Volume 20, Issue 4, 2024

Published on: 21 February, 2024

Page: [302 - 321] Pages: 20

DOI: 10.2174/011573398X283365240208195944

Price: $65

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Abstract

Cystic Fibrosis (CF) is a fatal hereditary condition marked by thicker mucus production, which can cause problems with the digestive and respiratory systems. The quality of life and survival rates of CF patients can be improved by early identification and individualized therapy measures. With an emphasis on its applications in diagnosis and therapy, this paper investigates how Artificial Intelligence (AI) is transforming the management of Cystic Fibrosis (CF). AI-powered algorithms are revolutionizing CF diagnosis by utilizing huge genetic, clinical, and imaging data databases. In order to identify CF mutations quickly and precisely, machine learning methods evaluate genomic profiles. Furthermore, AI-driven imaging analysis helps to identify lung and gastrointestinal issues linked to cystic fibrosis early and allows for prompt treatment. Additionally, AI aids in individualized CF therapy by anticipating how patients will react to already available medications and enabling customized treatment regimens. Drug repurposing algorithms find prospective candidates from already-approved drugs, advancing treatment choices. Additionally, AI supports the optimization of pharmacological combinations, enhancing therapeutic results while minimizing side effects. AI also helps with patient stratification by connecting people with CF mutations to therapies that are best for their genetic profiles. Improved treatment effectiveness is promised by this tailored strategy. The transformational potential of artificial intelligence (AI) in the field of cystic fibrosis is highlighted in this review, from early identification to individualized medication, bringing hope for better patient outcomes, and eventually prolonging the lives of people with this difficult ailment.

Keywords: Genetic test, machine learning, traditional diagnosis, imaging technology, biomarker, CFTR protein.

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