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Why Healthcare AI Is Needed Now

Here you‘ll find the resources needed to make the case for healthcare AI at your facility. It’s time to change the conversation from what AI could do to what it is doing every day to optimize operational efficiency for thousands of health systems around the world.

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The Business Case for Healthcare AI

There are few technologies that can directly impact costs, accessibility and quality while enhancing the user experience. The right AI can.

When intelligent AI is implemented as an enterprise-wide system, it can help individuals process large amounts of data, discover trends and accelerate decision making – enabling better outcomes and driving growth, even with fewer resources.

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Dive Deeper into Healthcare AI

Get a deeper understanding of the impact, challenges and opportunities within the realm of clinical AI through our eBook series.

AI for Clinicians = Accelerated, Accurate Decision Making Across Service Lines

See how an enterprise-wide healthcare AI strategy, powered by an AI operating system, has helped clinicals effectively manage patient data and workflows, enabling collective action across service lines to benefit health systems, clinicians and patients in numerous ways.

Healthcare AI Case Studies

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Acquires, analyzes and applies available AI to exams from available data sources, helping to identify candidates for admission or transfer.*

Automated Referral Network

Increase in Patient Volumes

72% more activations (PERT)1

Yale New Haven Health logo
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Alerts radiologists to critical patients to help manage workload and enable timely activation of clinical workflows.

Identify Suspected Abnormalities

Expanded Disease Awareness

16% improved quality of care with AI (PE)2

Envision Healthcare logo
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Exam results and EHR data available on a single platform for seamless communication and collective action.

Care Team Coordination

Improved Provider Satisfaction + Efficiency

55% Reduction in Turnaround Time (ICH)3

University of Rochester logo
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Reduced time to diagnosis and treatment helps improve outcomes

Prioritized Discharge

Shorter Length of Stay

26% Reduction in Length of Stay (PE)4

Cedars-Sinai logo
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Closed-loop system highlights patients who need follow-up

Patient Management

Reduced Readmissions

Average $400K annual cost savings at 13 sites5

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EXPLORE CLINICAL IMPACT

Uncover How AI is Changing Healthcare

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Amazon Expands Healthcare AI Ambitions
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Aidoc Announces Collaboration with AWS to Advance Clinical AI Foundation Models, Transforming Healthcare at Scale
Blog
Finding True North in AI: Why Healthcare Needs a Compass, Not a Quick Fix

Aidoc Staff
Blog
What Makes Aidoc’s Orchestration Agent Unique?

Alex Kane
Blog
The Governance and Security Risks Health Systems Need to Address Before AI Adoption

Yuval Segev
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AWS and General Catalyst Partner to Speed Up Development of Healthcare AI Tools
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AWS, General Catalyst Partner on Healthcare AI Tools
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General Catalyst, Amazon Web Services Form Partnership
Blog
Your PERT Team and AI: A Powerful Combination

Brandon Keys, BS, RVS
Blog
Top 5 Product Trends Shaping the Future of Clinical AI in 2025

Reut Yalon
Blog
What Would the Pioneers of Privacy Law Say About Clinical AI?

Yuval Segev
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Hartford HealthCare and Aidoc Partner to Transform Patient Care with Enterprise AI

Continue Your Healthcare AI Education

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AI Strategy

Blog

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Webinars

Have questions?
We’re here to help.

  1. Khosla A. (2022). Transforming Endovascular Care with AI-Triggered PE Response Teams [Webinar]. Aidoc. Available at aidoc.com.
  2. A. Jacob, B. Doan, C. Granville., (2022). Man and machine: implications of an artificial intelligence based algorithm in the detection of pulmonary embolism on computed tomography angiography. SIR 2022 Annual Meeting.
  3. Wismueller et al.(2020) A Prospective Randomized Clinical Trial for Measuring Radiology Study Reporting Time on Artificial IntelligenceBased Detection of Intracranial Hemorrhage in Emergent Care Head CT. Proceedings Volume 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 113170M doi: 10.1117/12.2552400
  4. 15 Petry M, Lansky C, Chodakiewitz Y, Maya M, Pressman B. Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System. Radiol Res Pract. 2022;2022:2141839. Published 2022 Aug 18. doi:10.1155/2022/2141839
  5. Aidoc. (2023). A Medicare Claims-Based Analysis Of The Impact Of AI On Readmission Rates. [White paper]

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