Insights

Clinical research summaries, radiology AI findings, and regulatory updates from the Diagnosify team.

Clinical Research
Apr 20, 2026
Multi-Center Trial Shows 97% Sensitivity in Chest X-Ray Pneumonia Detection

A prospective multi-center trial across eight academic medical centers demonstrates Diagnosify's chest X-ray model achieves 97% sensitivity for pneumonia detection with 91.4% specificity on a diverse patient cohort of 18,400 studies.

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Clinical Case Study
Apr 15, 2026
How AI-Assisted Radiology Caught What Three Radiologists Missed

A 6.2mm subpleural nodule flagged by our model after three board-certified radiologists signed off on consecutive reads — a case study in cognitive load, perceptual error patterns, and where AI second readers add measurable value.

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Perspective
Apr 8, 2026
The Case for AI-Assisted Radiology: What the Data Actually Shows

A systematic review of 34 peer-reviewed studies comparing AI-assisted versus unassisted radiologist reads, examining where AI adds measurable value, where it does not, and what questions remain open in the published literature.

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Regulatory
Apr 2, 2026
FDA Clearance for Diagnostic AI — The Timeline Nobody Warns You About

The official guidance says 90 days. Our first clearance took 14 months. A candid breakdown of predicate selection errors, Additional Information requests, PCCP requirements, and what post-market surveillance actually obligates you to do.

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Regulatory
Mar 25, 2026
FDA 510(k) Clearance: Our Path Through Regulatory Review

A detailed account of Diagnosify's 510(k) submission process — from predicate device selection and substantial equivalence arguments to clinical performance testing protocols and the final decision letter from the FDA Division of Radiological Health.

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Operations
Mar 18, 2026
Reducing Diagnostic Turnaround Time From Hours to Minutes

AI-assisted worklist triage cut median critical-study TAT from 68 minutes to 19 minutes at a Level I trauma center. Data from three deployment sites — a trauma center, community hospital, and teleradiology practice.

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Workforce
Mar 5, 2026
The Radiologist Shortage Is Real — Here's How AI Bridges the Gap

The United States faces a projected shortage of 42,000 radiologist FTEs by 2035. A clear-eyed analysis of where AI creates genuine clinical capacity — and the cases where it doesn't.

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Research & Ethics
Feb 20, 2026
Bias in Medical Imaging AI — What We Found and How We Fixed It

A 5.7-point sensitivity gap between white and Black patients in our chest X-ray pneumonia model — what caused it, the interventions that narrowed it to 1.2 points, and why demographic performance analysis should be mandatory.

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Implementation
Feb 5, 2026
Why Hospital IT Teams Push Back on AI Integration (And How to Win Them Over)

PACS compatibility, PHI handling, uptime SLAs, HITRUST reviews — the real objections from 14 hospital IT security assessments and what actually resolves them.

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Clinical Data
Jan 22, 2026
Comparing AI Sensitivity Across Chest X-Ray, CT, and MRI Modalities

Sensitivity and specificity figures across six detection tasks — with the validation set design, reference standard, and case-mix context that make cross-modality comparisons meaningful rather than misleading.

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Health Economics
Jan 8, 2026
The Economics of AI-Assisted Diagnostics for Community Hospitals

Community hospitals face different constraints than academic centers. A realistic ROI analysis covering software costs, teleradiology savings, locums reduction scenarios, and the volume thresholds where deployment makes financial sense.

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Company Journey
Dec 15, 2025
From Research Paper to Clinical Deployment — Our 18-Month Journey

What happens between a high-performing peer-reviewed model and a working clinical deployment — distribution shift, PACS integration failures, clinical governance, FDA review, and threshold calibration in sequence.

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Clinical Findings
Nov 12, 2025
What 50,000 AI-Flagged Studies Taught Us About False Positive Management

Alert fatigue, case-mix drift, normal variant misclassification, and the counterintuitive finding that fewer alerts sometimes means better clinical outcomes — from a 50,000-study post-market surveillance dataset.

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