All Next
All Next develops AI-driven clinical decision support and radiology platforms that integrate into existing healthcare workflows to improve diagnostic accuracy. Its AI-enhanced mammography screening tools have been shown to boost overall cancer detection by 29% and identify up to 45% more interval cancers compared to standard methods, supporting earlier disease identification and more confident treatment decisions.
- Healthcare Technology
- Artificial Intelligence
- Digital Health
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Radiologists face increasing workloads and must detect subtle abnormalities in medical imaging that can be missed by the human eye, leading to delayed diagnoses and less confident treatment decisions. Standard mammography screening alone fails to identify a significant portion of cancers, particularly interval cancers that appear between routine screenings.
Solution
All Next provides AI-powered diagnostic platforms that integrate into clinical workflows to enhance radiologists' accuracy and efficiency. The technology analyzes medical scans with high precision, detecting subtle patterns that may escape human observation and delivering quantitative assessments that support clinical decision-making. The AI systems continuously learn and refine their diagnostic capabilities with each case, providing increasingly reliable second opinions that complement radiologists' expertise. The solutions are designed for real-world utility, safety, and compliance, enabling seamless adoption in radiology practices and health systems.
Target Audience
Primary users are radiologists and healthcare providers who need AI-assisted tools to improve diagnostic accuracy and efficiency in medical imaging, as well as health systems seeking to expand access to quality care through advanced diagnostic technology.
Features
- AI-enhanced mammography screening that boosts overall cancer detection by 29% and identifies up to 45% more interval cancers compared to standard methods
- Quantitative imaging assessments that support earlier disease identification and treatment response evaluation
- Continuous machine learning that refines diagnostic accuracy with each analyzed case
- Clinical decision support tools designed to integrate directly into existing healthcare workflows
- Focus on safety, compliance, and real-world utility to support responsible clinical adoption