← Search

Data · dataset · 2025

Revolutionizing COPD and Asthma Management with Artificial Intelligence

Listed in Teesside University Research Data Repository

Description

Revolutionizing COPD and Asthma Management with Artificial Intelligence Yudi Kurniawan Budi Susilo1*, Shamima Abdul Rahman2, 1Faculty of Business and Technology, University of Cyberjaya, 63000 Cyberjaya , Selangor, Malaysia 2Centre for Research and Graduate Studies, University of Cyberjaya, 63000 Cyberjaya , Selangor, Malaysia Authors’ email: yudi299@gmail.com*, shamima@cyberjaya.edu.my *Corresponding author

Abstract

Read the rest (3 more)

The integration of artificial intelligence (AI) into the management of chronic obstructive pulmonary disease (COPD) and asthma offers significant advancements in patient care, diagnosis, and treatment personalization. AI technologies, particularly machine learning and deep learning, have shown great promise in predictive modeling, enabling earlier detection and more accurate diagnoses. AI-driven tools, such as telemedicine and remote monitoring applications, are helping clinicians provide personalized care and manage these conditions more effectively, especially for high-risk patients.

Additionally, AI's ability to analyze vast datasets, including electronic health records and medical imaging, allows for more dynamic and adaptive treatment plans tailored to individual patients' needs. However, challenges remain, such as ensuring data privacy, addressing ethical concerns, and developing standardized regulatory frameworks to support the implementation of AI in clinical settings. Despite these challenges, the potential of AI to revolutionize COPD and asthma management is vast, and continued research and collaboration will be critical in overcoming these barriers and enhancing healthcare outcomes for patients worldwide.

Keyword: Artificial Intelligence (AI), Chronic Obstructive Pulmonary Disease (COPD), Asthma Management, Machine Learning (ML), Remote Monitoring

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Disease 75% · Imaging 75%
Provenance · 1 source records, 13 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/9z8k2f95f6.218 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[disease].local:disease:diseaseenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
concepts[field].anzsrc:group:4602mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Artificial Intelligence']
concepts[field].anzsrc:group:4611mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Machine Learning']
concepts[field].local:field:computer-science-aimapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:medicine-healthmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:imagingenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title