The medical AI market has matured. It’s no longer enough to boast benchmark-beating algorithms. Hospitals and imaging centers now want something more practical: AI that works inside existing systems without slowing clinicians down.

That’s the premise behind a new partnership between Coreline Soft and INFINITT North America, which has delivered a fully automated, “zero-click” AI reading solution now live in U.S. radiology practices.

Instead of asking radiologists to jump between dashboards or sign into yet another platform, the companies have embedded Coreline’s AVIEW AI directly into the INFINITT PACS environment. The result: AI-powered insights appear natively within the radiologist’s existing workflow—no extra logins, no manual triggers, no workflow detours.

In a field where seconds matter and cognitive load is high, that detail is more than cosmetic. It’s strategic.

From Algorithm Accuracy to Operational Infrastructure

The global medical AI conversation has shifted over the past five years. Early entrants focused heavily on detection rates and sensitivity metrics. But clinical adoption has lagged when tools disrupted established reading patterns.

Radiologists don’t want another screen. They want smarter readings inside the one they already use.

By deeply embedding Coreline’s AVIEW platform into INFINITT PACS, the integration transforms AI from an optional add-on into background infrastructure. The system automatically:

• Performs coronary artery calcium (CAC) scoring

• Enhances lung nodule detection

• Reduces overall case reading times

For high-volume radiology groups processing more than 6,000 cases per quarter, these efficiencies compound quickly.

A “Zero-Click” Model in Practice

The first U.S. site to adopt the solution, ImageCare Radiology, reported a rapid rollout across its network—completed within one month. According to its leadership, the impact was immediate in both speed and diagnostic accuracy.

The phrase “zero-click” isn’t marketing fluff here. It signals something critical: the AI activates without user intervention.

That matters because adoption in radiology often fails at the friction point. Even small workflow disruptions can stall usage. By eliminating manual triggers and secondary interfaces, the system keeps the radiologist’s attention on interpretation rather than navigation.

This approach aligns with broader industry trends. Enterprise AI vendors in healthcare are increasingly pursuing deep PACS and EHR integrations rather than standalone AI dashboards. The goal is invisible intelligence, not visible complexity.

Revenue Impact: From Detection to Follow-Up

Beyond clinical metrics, the integration carries financial implications.

Improved detection sensitivity and automated CAC scoring can increase downstream follow-up exams. In value-based care environments and screening programs, that translates directly into measurable ROI.

For imaging networks handling thousands of cases quarterly, even modest increases in follow-up rates can create meaningful revenue uplift. AI that identifies more actionable findings doesn’t just improve care—it expands billable opportunities.

That dual impact—clinical performance plus financial return—is becoming a decisive factor in AI procurement decisions.

The INFINITT Integration Suite: Built for U.S. Reimbursement

To accelerate adoption in the U.S., Coreline Soft has launched the INFINITT Integration Suite, a dedicated package tailored specifically for INFINITT users.

The suite enables:

• Rapid deployment of AI modules

• Support for CPT-based reimbursement

• Fully automated, hands-free workflows

Reimbursement alignment is particularly important in the U.S. healthcare system, where financial viability often dictates technology adoption. By incorporating CPT code support, the companies are addressing a common bottleneck in AI commercialization.

Instead of forcing radiology groups to navigate reimbursement uncertainty, the integration is designed to plug directly into established billing structures.

A Competitive Thoracic AI Portfolio

Coreline Soft isn’t stopping at workflow integration. The company is positioning its broader thoracic AI portfolio for visibility at the 2026 annual meeting of the Society of Thoracic Radiology.

The lineup includes:

• AVIEW LCS, positioned as a “First Reader” solution for lung cancer screening

• AVIEW Lung Texture for interstitial lung disease (ILD)

• AVIEW COPD for chronic obstructive pulmonary disease assessment

The portfolio also emphasizes Opportunistic Screening—extracting multiple clinical insights from a single low-dose CT scan. That means simultaneously evaluating:

• Lung cancer risk

• COPD indicators

• Cardiovascular risk markers

This multi-condition analysis from one imaging study reflects a growing industry push toward comprehensive, AI-enhanced diagnostic value from existing scans.

Why This Matters in 2026

Radiology is under mounting pressure. Workforce shortages persist, imaging volumes continue to rise, and demand for screening programs—particularly lung cancer screening—is expanding.

At the same time, AI vendors are proliferating.

What differentiates this deployment is not simply detection capability but operational embedment. In an increasingly crowded AI imaging market, seamless integration may matter more than marginal gains in sensitivity.

Healthcare IT buyers are asking new questions:

• Does the AI fit into existing PACS systems?

• Can it scale across multi-site networks quickly?

• Does it support reimbursement models?

• Will clinicians actually use it?

By eliminating friction, Coreline Soft and INFINITT are attempting to answer all four at once.

The Bigger Trend: Invisible AI Wins

The most successful AI in healthcare may be the least noticeable.

As the market evolves from pilot programs to production environments, solutions that operate quietly inside established systems—rather than demanding attention—are likely to win.

The “zero-click” approach signals a shift in medical AI maturity. Instead of asking clinicians to adapt to software, vendors are adapting software to clinicians.

If this model scales beyond early adopters, it could set a new baseline for how imaging AI is delivered in U.S. radiology practices.

And in a field where workflow efficiency and diagnostic precision are both mission-critical, invisible intelligence may be the smartest innovation of all.

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