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Last Updated: Apr 25, 2025 | Study Period: 2024-2030
AI algorithms that can identify ever-smaller lung tumours have been developed in response to the requirement for early diagnosis. Because of the limitations of human eyesight, radiologists are prone to overlooking small cancerous tumours. For example, up to 35% of lung nodules are overlooked during the first examination.
AI technology can help on both counts by taking part of the load off of overworked professionals and finding lung spots that aren't evident to the human eye. Computer-assisted diagnostic technologies are already used by radiologists to help them detect malignant tumours.
| S No | Overview of Development | Development Detailing | Region of Development | Possible Future Outcomes |
| 1 | Siemens signed an agreement with Geisinger, a healthcare provider | Access to diagnostic imaging equipment and artificial intelligence applications was the focus of the deal. | Global | This would enhance better Technological Controls |
| 2 | Aidoc teamed up with LucidHealth, a physician-owned and led radiology company | The goal of this partnership was for the latter firm to deploy an AI-powered diagnostic tool developed by the former to assist prioritise and speed treatment for patients with urgent, life-threatening diseases. | Global | This would enhance better Technological Controls |
| 3 | Zebra Medical Vision announced its collaboration with Johnson & Johnson's DePuy Synthes. | The goal of the partnership was to provide Cloud-based AI solutions to the orthopaedic and bone health industries together. | Global | This would enhance better Technological Controls |
| 4 | AI and machine learning could improve cancer diagnosis through biomarker discovery | These technologies are now being used to tackle the problems of cancer biomarker identification, where the analysis of massive volumes of imaging and molecular data exceeds the capabilities of classic statistical analyses and tools. | Global | This would enhance better Technological Controls |
| 5 | Artificial Intelligence System Improves Breast Cancer Detection | Scientists from NYU and NYUAD have built a revolutionary artificial intelligence (AI) system that reaches radiologist-level reliability, according to a recent study. | Global | This would enhance better Technological Controls |
The Global AI Powered Cancer Diagnostic Market accounted for $XX Billion in 2023 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
Scientists are discovering new methods to use artificial intelligence (AI) in the healthcare area as it keeps expanding. AI has played a key role in the diagnosis, decision-making, and treatment of chronic diseases, particularly in medical research.
AI integration in precision medicine might enhance diagnostic efficiency and accuracy, help healthcare decision, and result in improved healthcare outcomes. Clinical care driven by AI has the potential to significantly reduce health inequities, especially in the low environments.
GE Healthcare a leading mobiliser of the Mobility solutions involving cancer solutions orienting towards AI Cancer requirements in the market. It detects and assesses the likelihood of malignancy in a lung nodule, which is crucial for assessing whether or not a biopsy is required and for speeding up diagnosis.
It's the first AI-assisted diagnostic programme approved by the FDA for early-stage lung cancer, and it's been demonstrated to enhance the high sensitivity of undetermined nodular aggressiveness evaluations.
Siemens AG is part of the component manufacture trending companies in the current industry. Its latest addition has been brought in through the AI-Pathway Companion Lung Cancer aids multidimensional teams (MDT) by centralising patient care and case reviews on an unified platform, offering data quality assurance, and allowing for the production of clinically important patient-specific footnotes.This is a waste of time and effort for all MDT participants.
| Sl no | Topic |
| 1 | Market Segmentation |
| 2 | Scope of the report |
| 3 | Abbreviations |
| 4 | Research Methodology |
| 5 | Executive Summary |
| 6 | Introduction |
| 7 | Insights from Industry stakeholders |
| 8 | Cost breakdown of Product by sub-components and average profit margin |
| 9 | Disruptive innovation in the Industry |
| 10 | Technology trends in the Industry |
| 11 | Consumer trends in the industry |
| 12 | Recent Production Milestones |
| 13 | Component Manufacturing in US, EU and China |
| 14 | COVID-19 impact on overall market |
| 15 | COVID-19 impact on Production of components |
| 16 | COVID-19 impact on Point of sale |
| 17 | Market Segmentation, Dynamics and Forecast by Geography, 2024-2030 |
| 18 | Market Segmentation, Dynamics and Forecast by Product Type, 2024-2030 |
| 19 | Market Segmentation, Dynamics and Forecast by Application, 2024-2030 |
| 20 | Market Segmentation, Dynamics and Forecast by End use, 2024-2030 |
| 21 | Product installation rate by OEM, 2023 |
| 22 | Incline/Decline in Average B-2-B selling price in past 5 years |
| 23 | Competition from substitute products |
| 24 | Gross margin and average profitability of suppliers |
| 25 | New product development in past 12 months |
| 26 | M&A in past 12 months |
| 27 | Growth strategy of leading players |
| 28 | Market share of vendors, 2023 |
| 29 | Company Profiles |
| 30 | Unmet needs and opportunity for new suppliers |
| 31 | Conclusion |
| 32 | Appendix |
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