Lung Cancer Diagnosis Using AI:
Closing the Detection-Timing Gap
This report offers an in-depth, data-backed analysis of AI-based lung cancer diagnosis, covering the patent landscape, assignee positioning, technology fragmentation, market structure, key players and strategic outlook, built for teams that need more than a surface-level overview to make informed decisions.
You've read the summary. Here's what it left out.
The short report gives you the headline story. The long report gives you the full analysis, the assignee-level datasets, technology fragmentation, and the complete market intelligence that patent attorneys, R&D leaders and investors actually need to brief clients or leadership.
The numbers shaping AI-based lung cancer diagnosis
Patent Families Mapped
The report maps nearly 2,000 active INPADOC patent families in AI-based lung cancer diagnosis, with more than 87% filed after 2016.
China Leads Filings
China accounts for 40.6% of patent filings, followed by the US at 19.7% and India at 12.1%, highlighting the geographic concentration of diagnostic AI innovation.
Low Grant Rate
Only 12.6% of analysed patents have been granted, pointing to a rapidly developing and still-maturing AI lung cancer diagnostics IP landscape.
Genetic Marker Patents
Genetic markers represent the largest biomarker category, with 837 patent assets, followed by proteins at 364 and cfDNA at 243.
CT Patent Assets
CT-based technologies lead the imaging landscape with 546 patent assets, ahead of X-ray, MRI and PET-based approaches.
AI Diagnostic Accuracy
AI algorithms covered in the report have demonstrated up to 97% accuracy in classifying lung cancer types from tissue samples, highlighting the potential of AI-enabled diagnosis.
Designed for Decision-Makers Across AI Lung Cancer Diagnosis
Lung Cancer Diagnosis Using AI: Long Report
- Nearly 2,000 active INPADOC patent families mapped across AI-based lung cancer diagnosis
- Detailed patent filing, grant, legal-status and jurisdictional analysis
- Top patent holders and assignee-level competitive intelligence
- Portfolio and filing analysis across China, US, India and other major jurisdictions
- Detailed technology taxonomy covering CT, X-ray, MRI, PET, ultrasound, spectroscopy and pathology
- Biomarker and sample analysis covering genetic markers, proteins, cfDNA, blood, urine, sputum and breath
- AI/ML technology mapping across SVM, random forest, logistic regression, CNNs, transformers, LLMs and reinforcement learning
- Market size and forecast analysis for lung cancer diagnostics and AI in cancer diagnostics
- Key AI diagnostic products and market players
- FDA approval and clinical-development landscape for AI-based diagnostic technologies
- M&A, licensing deals, joint ventures and university collaborations
- Emerging opportunity areas including liquid biopsy, cfDNA, breath-based diagnostics, sputum analysis and AI-powered imaging
- Competitive insights into where diagnostic IP is concentrated and where emerging technologies are gaining traction