Author
Fractify Clinical AI Research Team
A multidisciplinary team of clinical AI researchers, radiologists, and ML engineers building diagnostic imaging AI at Databoost Sdn Bhd, Kuala Lumpur. Our systems achieve up to 97.9% accuracy on Brain MRI tumor detection and analyse 18+ pathologies on chest X-ray in under 3 seconds.
97.9%
Brain MRI accuracy
18+
X-Ray pathologies
<3s
Analysis time
Recent Articles
enterprise
PACS AI Integration: What the IT Team Must Know Before Go-Live
radiology ai adoption is accelerating across hospital networks, but most delayed go-lives share a single root cause: the clinical team approved the AI, the vendor delivered the software, and the IT department opened the integration specifications for the first time on deployment …
enterprise
AI Radiology Procurement: The Hospital IT Director Checklist
Hospitals that deploy AI radiology tools without structured procurement evaluation report a 43% higher rate of workflow abandonment within 12 months — almost always for the same reason: the procurement team evaluated the demo, not the integration. A system achieving 97.9% brain M…
enterprise
AI Radiology Implementation Timeline: Realistic 90-Day Guide
The question every hospital CIO asks after signing an AI radiology contract is immediate and reasonable: when can we go live? The honest answer — one that vendors frequently soften — is 90 days, assuming no major infrastructure surprises. A 30-day promise describes a demo environ…
enterprise
Cloud vs On-Premise AI Radiology: Total Cost of Ownership for Mid-Size Hospitals
A mid-size hospital—defined here as 200 to 600 beds processing 300 to 1,200 DICOM studies per day—typically receives AI radiology proposals that quote either a monthly SaaS fee or a one-time licence plus hardware cost. Neither figure represents total cost of ownership. The monthl…
enterprise
5 Red Flags in an AI Radiology Vendor Proposal (and How to Spot Them)
AI radiology procurement is structurally different from buying traditional medical devices. A CT scanner's specifications are standardised and verifiable. An AI radiology platform's claims—97% accuracy, real-time processing, seamless PACS integration—are asserted in prose and rar…
enterprise
AI Radiology ROI Calculator: What Hospitals Actually Measure in Year One
Most AI radiology vendors quote turnaround time. A few mention radiologist throughput. Almost none address the three measurement tracks that actually determine whether the board renews the contract: missed-finding liability exposure, downstream cost avoidance from earlier diagnos…