AI in Respiratory Diseases Market Size is predicted to witness a 29.4% CAGR during the forecast period for 2025-2034.
AI is revolutionizing the field of respiratory diseases by aiding in early diagnosis, personalized treatment, and remote monitoring. It can analyze medical images, predict disease progression, and even assist in drug discovery. AI also helps patients manage conditions like asthma and COPD while monitoring air quality and providing real-time insights. These advancements hold promise for improving patient care and outcomes in respiratory health.
Clinical data, chest scans, lung pathology, and pulmonary function testing can all be used by AI to aid in the diagnosis and prognosis of pulmonary disorders. The advent of new digital tools drives market expansion, and fields like genomics, medical imaging, and electronic health records are contributing to an unprecedented explosion in the volume and complexity of healthcare-related data. Because of this explosive expansion, more and more clinically relevant applications based on AI have been developed.
Expert pulmonologists who have studied AI theory and practice will be in a strong position to exploit emerging career prospects in both clinical practice and academic research. This review aims to educate pulmonologists and other interested readers about artificial intelligence's potential applications in this field of medicine. The advancement of healthcare technology has led to an anticipated uptick in the use of AI in respiratory diseases.
However, several negative aspects seriously restrain the expansion of AI in the respiratory diseases market. Lack of knowledge and high cost are hindering the AI in respiratory diseases market growth. In addition, the COVID-19 pandemic has had a major effect on the market for providers of artificial intelligence in respiratory diseases medicine. Several factors have contributed to this effect. Genomics, diagnostics, drug development, and individualized treatment are just some of the areas where artificial intelligence technologies like deep learning and the processing of natural language have found use. During the recent COVID-19 epidemic, the value of AI in responding to medical emergencies and improving our understanding of complex diseases became clear.
The AI in respiratory diseases market is segmented based on the indication, imaging type, and end-use. As per the indication, the market is segmented into chronic obstructive pulmonary disease, interstitial lung disease, and pulmonary infection. By imaging type, the market is segmented into MRI, CT Scan, and ePRO. According to end-use segment, the market is segmented into hospitals, diagnostic centres, ambulatory surgical centers, and others.
The CT Scan AI in the respiratory diseases category is expected to hold a maximum global market share because it helps in the diagnosis of lung problems such as pneumonia, cancer, blood clots, and smoking-related damage.
The diagnostic centers are expected to grow rapidly in the global AI in respiratory diseases market. The crucial role of diagnostic centers in the diagnosis of diseases at an early stage cannot be overstated. Early diagnosis is solution to the successful treatment of different diseases, including cancer, cardiovascular disease. Screening tests and preventative medical examinations are available at medical clinics that specialize in diagnosing and treating such conditions, especially in countries like the US, Germany, the UK, China, and India.
The North American AI in respiratory diseases market activity is anticipated to record the largest market share in revenue in the near future. It can be attributed to the expansion of financial resources and time spent on R&D. As the need for innovative healthcare services grows, governments, institutions, and investors are pouring more money into projects that aim to apply artificial intelligence to the practice of respiratory disease medicine. The need for AI in Respiratory Diseases is anticipated to increase as a result of this region.
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Report Attribute |
Specifications |
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Growth Rate CAGR |
CAGR of 29.4% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Indication, Imaging Type, End-Use |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia |
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Competitive Landscape |
Siemens Healthineers, VIDA Diagnostics Inc,THIRONA, Infervision, icometrix. GE Healthcare, Philips Healthcare, Others |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Respiratory Diseases Market Snapshot
Chapter 4. Global AI in Respiratory Diseases Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Indication Estimates & Trend Analysis
5.1. By Indication, & Market Share, 2024 & 2034
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Indication:
5.2.1. Chronic Obstructive Pulmonary Disease
5.2.2. Interstitial Lung Disease
5.2.3. Pulmonary Infection
Chapter 6. Market Segmentation 2: By Imaging Type Estimates & Trend Analysis
6.1. By Imaging Type & Market Share, 2024 & 2034
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Imaging Type:
6.2.1. MRI
6.2.2. CT Scan
6.2.3. ePRO
Chapter 7. Market Segmentation 3: By End-use Estimates & Trend Analysis
7.1. By End-use & Market Share, 2024 & 2034
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By End-use:
7.2.1. Hospitals
7.2.2. Diagnostic Centers
7.2.3. Ambulatory Surgical centers
7.2.4. Others
Chapter 8. AI in Respiratory Diseases Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America AI in Respiratory Diseases Market revenue (US$ Million) estimates and forecasts By Indication, 2021-2034
8.1.2. North America AI in Respiratory Diseases Market revenue (US$ Million) estimates and forecasts By Imaging Type, 2021-2034
8.1.3. North America AI in Respiratory Diseases Market revenue (US$ Million) estimates and forecasts By End-use, 2021-2034
8.1.4. North America AI in Respiratory Diseases Market revenue (US$ Million) estimates and forecasts by country, 2021-2034
8.2. Europe
8.2.1. Europe AI in Respiratory Diseases Market revenue (US$ Million) By Indication, 2021-2034
8.2.2. Europe AI in Respiratory Diseases Market revenue (US$ Million) By Imaging Type, 2021-2034
8.2.3. Europe AI in Respiratory Diseases Market revenue (US$ Million) By End-use, 2021-2034
8.2.4. Europe AI in Respiratory Diseases Market revenue (US$ Million) by country, 2021-2034
8.3. Asia Pacific
8.3.1. Asia Pacific AI in Respiratory Diseases Market revenue (US$ Million) By Indication, 2021-2034
8.3.2. Asia Pacific AI in Respiratory Diseases Market revenue (US$ Million) By Imaging Type, 2021-2034
8.3.3. Asia Pacific AI in Respiratory Diseases Market revenue (US$ Million) By End-use, 2021-2034
8.3.4. Asia Pacific AI in Respiratory Diseases Market revenue (US$ Million) by country, 2021-2034
8.4. Latin America
8.4.1. Latin America AI in Respiratory Diseases Market revenue (US$ Million) By Indication, (US$ Million) 2021-2034
8.4.2. Latin America AI in Respiratory Diseases Market revenue (US$ Million) By Imaging Type, (US$ Million) 2021-2034
8.4.3. Latin America AI in Respiratory Diseases Market revenue (US$ Million) By End-use, (US$ Million) 2021-2034
8.4.4. Latin America AI in Respiratory Diseases Market revenue (US$ Million) by country, 2021-2034
8.5. Middle East & Africa
8.5.1. Middle East & Africa AI in Respiratory Diseases Market revenue (US$ Million) By Indication, (US$ Million) 2021-2034
8.5.2. Middle East & Africa AI in Respiratory Diseases Market revenue (US$ Million) By Imaging Type, (US$ Million) 2021-2034
8.5.3. Middle East & Africa AI in Respiratory Diseases Market revenue (US$ Million) By End-use, (US$ Million) 2021-2034
8.5.4. Middle East & Africa AI in Respiratory Diseases Market revenue (US$ Million) by country, 2021-2034
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. ArtiQ
9.2.2. Dectrocel Healthcare
9.2.3. DeepMind Health
9.2.4. GE Healthcare
9.2.5. Icometrix
9.2.6. Infervision
9.2.7. Philips Healthcare
9.2.8. PneumoWave
9.2.9. Respiray
9.2.10. Siemens Healthineers
9.2.11. Swaasa AI
9.2.12. THIRONA
9.2.13. Verily
9.2.14. VIDA Diagnostics Inc
9.2.15. Zynnon
AI in Respiratory Diseases Market By Indication-
AI in Respiratory Diseases Market By Imaging Type -
AI in Respiratory Diseases Market By End-use -
AI in Respiratory Diseases Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
