Calibrated for screening mammography
Estimate the value of intelligent reliability on your AI.
What Nambi adds
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Annual operational value
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total per year
Radiologist hours reclaimed
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per year
False positives prevented
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per year
Show the math
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Sources & assumptions
- Missed cases per 10K (FN rate). Cancer prevalence in screening mammography ~0.5% × AI sensitivity gap ~10% = ~5 missed per 10K cases on AI alone. Sensitivity benchmarks: McKinney et al, Nature 2020; Lång et al, MASAI Lancet Oncol 2023.
- AI false-positive rate. Dembrower et al, ScreenTrustCAD HAI, Radiology 2025. AI-only flags reach downstream recall in ~4.6% of cases. Paper
- Cost per missed case. Treatment cost differential late-stage vs early-stage breast cancer: ~$60–85K (Blumen, Fitch, Polkus, Am Health Drug Benefits 2016; PMC4822976). Probability-weighted litigation expectation: ~$15–30K (Whang et al, Radiology 2013, paper; Berlin, AJR 2003).
- Cost per FP workup. CMS CPT reimbursement schedules for diagnostic mammogram (77065/77066), breast ultrasound (76641), and biopsy procedures.
- Selective-deferral literature: Dvijotham et al, “Enhancing diagnostic accuracy of medical AI via selective deferral,” Nature Medicine 2023, showed a 25% false-positive reduction and 66% clinician-workload reduction when ~30% of cases were deferred to humans.
- Radiologist wage. BLS Occupational Employment & Wage Statistics, May 2024 (29-1224).
- Radiologist time per case. Industry estimate for screening mammography (1–3 min/case); adjustable to match your institution.