Northwestern Medicine

by Northwestern Medicine  · Based in United States → — Patients First
Cardiology Neurology Oncology
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Overview

Northwestern Medicine has developed a generative AI system, known as the Automated Radiology Interpretation Evaluation System (ARIES), designed to assist radiologists. This tool is intended for use by radiologists in various care settings, particularly those dealing with high volumes of imaging studies across an integrated health system.

ARIES integrates into the clinical workflow by analyzing X-rays and CT scans to generate draft radiology reports that are approximately 95% complete. Radiologists then review and finalize these reports. The system also includes a feature that monitors for critical findings and cross-references them with patient records, alerting radiologists to serious conditions.

Notable capabilities include its ability to process all types of X-rays and CT scans, rather than focusing on a single condition. Studies have indicated that the tool can increase report completion efficiency, with some radiologists experiencing significant gains. Northwestern Medicine is also working on expanding ARIES to support MRI and ultrasound imaging.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Accelerated image interpretation
  • Enhanced diagnostic accuracy
  • Generative AI capabilities
  • Potential for early disease detection
  • Streamlined radiology workflows

Use Cases

  • Assisting radiologists in image analysis
  • Improving diagnostic efficiency
  • Supporting clinical decision-making in radiology
  • Reducing radiologist workload
  • Enhancing patient care through faster diagnoses

What Physicians Need to Know

Evidence Base
The AI model was developed in-house by Northwestern Medicine physicians and engineers using clinical data from their 11-hospital network. It was built from scratch, rather than adapting existing large language models. The system also incorporates natural language processing (NLP) to analyze radiology reports.
Clinical Validation Studies
A major clinical study across an 11-hospital Northwestern Medicine network analyzed nearly 24,000 radiology reports over five months. The study showed an average 15.5% increase in report completion efficiency, with some radiologists achieving gains as high as 40%, without compromising accuracy. Unpublished follow-on work indicates efficiency gains of up to 80% for CT scans. The AI system also demonstrated the ability to flag serious conditions like pneumothorax with a sensitivity of 72.7% and specificity of 99.9% among almost 98,000 screened studies. Priority flags were available in a median of 24 seconds, compared to 24.5 minutes for radiologist notification.
Alert Fatigue Management
The AI system is designed to identify critical findings and cross-check them with patient records, issuing alerts to radiologists for serious detections. For incidental findings, the AI triggers alerts in the EHR to the ordering physician and tracks completion of recommended follow-ups, sending additional alerts if action isn't taken. This system aims to streamline care coordination and reduce the burden on clinicians.
Differential Diagnosis Support
The AI model takes a holistic approach, reviewing an entire X-ray or CT scan and producing a report that is approximately 95% complete and tailored to the patient and radiologist's preferred reporting style. It can identify serious problems like pneumothorax before a radiologist even opens the image. The team is also adapting the AI model to detect potentially missed or delayed diagnoses, such as early-stage lung cancer.
Clinical Workflow Integration
This generative AI radiology tool is integrated into the real clinical workflow, making it the first of its kind. The AI system drafts reports, which radiologists then review and finalize. For incidental findings, the AI integrates with the EHR to trigger Best Practice Advisories (BPAs) that display findings and recommended follow-ups directly in the ordering physician's workflow. The system also notifies patients via their online portal and involves a dedicated follow-up team for those without an established physician or portal access.
Decision Audit Trail
The system tracks the completion of recommended follow-ups for both incidental and expected findings. If follow-up action is not taken, another alert is sent.
Physician Tip

Leverage the AI-generated draft reports as a significant head start, allowing you to focus on critical review and personalization. Pay close attention to the AI's alerts for urgent findings, as these are designed to accelerate triage and potentially life-saving interventions. Remember that the AI is a tool to augment, not replace, your clinical judgment; your expertise remains the gold standard for final diagnosis and treatment decisions. Utilize the system's follow-up tracking for incidental findings to ensure comprehensive patient care and reduce the risk of missed diagnoses.

The AI system is deeply integrated with the Electronic Health Record (EHR) to provide alerts and notifications directly within the physician's workflow. It also cross-checks critical findings with patient records. The in-house development approach allows for tailored integration within the Northwestern Medicine network and its specific clinical data. Future expansions are planned to support MRI and ultrasound imaging.

Details

Category Clinical Decision Support & Reference, Radiology & Imaging AI
Pricing Unknown — unknown
DeploymentOn-premise (within their 11-hospital network)
Mobile App1
LanguagesEnglish
TrainingUnknown
Target SizeLarge hospital systems
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated

Two patents have been approved for their generative AI radiology technology, and others are in various stages of the approval process. The tool is in the early stages of commercialization.
GDPRUnknown AI-estimated
Integrations
EHR Not specified
Specialties Cardiology, Neurology, Oncology, Radiology

Social Proof

Customersunknown
Notable
Northwestern Medicine

Support & Reliability

Training ProvidedUnknown

What the Web Says

Northwestern Medicine has developed an in-house generative AI tool for radiology that significantly boosts productivity and identifies life-threatening conditions rapidly. Physicians report a substantial increase in efficiency, with some experiencing up to an 80% gain, without compromising diagnostic accuracy. The tool is designed to assist, not replace, radiologists and is being commercialized.

Overall: Positive

Strengths

  • Significantly increases radiologist productivity and efficiency (average 15.5%, up to 80% in some cases).
  • Maintains high diagnostic accuracy and report quality.
  • Rapidly identifies life-threatening conditions like pneumothorax, enabling quicker treatment.
  • Generates nearly complete, personalized radiology reports, reducing radiologist workload.
  • Cost-effective solution developed in-house, making advanced AI accessible to typical health systems.
  • Holistic model analyzes entire X-rays and CT scans for various clinical issues, unlike many single-condition AI tools.

Limitations

  • Some employees report being short-staffed at times.
  • Concerns about inconsistent leadership, limited training, and uneven workload distribution in some departments.
  • Some Reddit users express disappointment with patient care coordination and communication in certain areas.
  • Perception of management prioritizing metrics and money over employee well-being in some IT and patient care roles.
  • One Reddit user reported an issue with billing and incorrect CPT codes.
  • Some employees feel pay is not competitive in software development roles.

Based on reviews from: Northwestern Medicine News, Indeed.com, Reddit, Becker's Hospital Review, Healthgrades, TechFinitive, MedTech Dive, Perplexity

Last updated: 2026-06-22

Ratings & Reviews

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Ease of Use
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Press & Coverage

Northwestern Medicine News
How Generative AI Is Transforming Radiology at Northwestern Medicine
Northwestern Medicine has developed a first-of-its-kind generative AI system that is revolutionizing radiology by boosting productivity, identifying serious health problems quickly, and offering a cost-effective solution to the radiologist shortage. The in-house developed tool generates nearly complete radiology reports from X-rays and CT scans, significantly improving efficiency without compromising accuracy.
2026-03
HOSPITALS Magazine
Advancing Patient Care Through AI: Northwestern Medicine's Strategic Approach
Northwestern Medicine is strategically integrating AI into clinical and operational workflows to enhance diagnostic accuracy, streamline operations, and improve patient outcomes. Their in-house developed Automated Radiology Interpretation Evaluation System (ARIES) generates draft reports for X-rays and CT scans in seconds, and they also utilize FDA-approved AI for colonoscopies.
2025-12
Radiology Business
Real-world use of generative AI boosts radiologist productivity by up to 40%
A study published in JAMA Network Open details how Northwestern Medicine's in-house generative AI system for radiology has boosted radiologist productivity by up to 40% without compromising accuracy. The system analyzes entire images and generates personalized reports, and is in the early stages of commercialization.
2025-06
Health IT Answers
Northwestern Medicine Pioneers Generative AI Radiology Tool, Boosting Efficiency Without Sacrificing Accuracy
Northwestern Medicine's custom-built generative AI system has significantly improved radiologist productivity by as much as 40% while maintaining high accuracy. The AI model generates near-complete, patient-specific radiology reports from X-rays and is the first such tool integrated into live clinical workflows.
2025-08
Illinois Public Media
Northwestern Medicine using cutting-edge AI technology that could be game changer for certain surgeries | The 21st Show | Illinois Public Media
Northwestern Medicine is developing 'digital twins' using AI to simulate diseases and test treatment plans on virtual patients before administering them to actual patients, aiming for more personalized medicine.
2026-05
Northwestern Medicine
Northwestern Medicine and Founders Factory to scale European AI ventures into America's leading health system
Northwestern Medicine is partnering with global startup accelerator Founders Factory to bring top UK and European AI founders to the US health market. This collaboration aims to advance new models of patient care, supercharge research, and deliver operational efficiencies through AI-enabled technologies.
2026-02
PR Newswire
Northwestern Medicine Collaborates with Vizlitics to Advance Cancer Clinical Trial Recruitment and Real-World Data
Northwestern Medicine is collaborating with Vizlitics, a healthcare AI company, to deploy next-generation AI tools for cancer clinical trial recruitment and real-world data management. This partnership aims to improve trial matching, streamline research operations, and expand access to clinical trials for cancer patients.
2026-06
Siemens Healthineers Press Release
Northwestern Medicine and Siemens Healthineers Launch Strategic Collaboration to Transform Cancer Care
Northwestern Medicine and Siemens Healthineers have initiated a strategic collaboration to redefine diagnostics and cancer care. This multi-year partnership will focus on accelerating innovation in imaging, theranostics, interventional radiology, and radiation oncology to deliver a new standard of precision care.
2026-02

Videos

Product demos, reviews, and walkthroughs for Northwestern Medicine.

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Frequently Asked Questions

Northwestern Medicine's CDS system is designed to integrate directly into our Epic EHR, providing real-time alerts and recommendations within the physician's existing workflow. We continuously monitor compliance rates through system analytics, and while specific numbers vary by specialty and alert type, we strive for high adoption through user-friendly interfaces and evidence-based recommendations.
While our primary CDS is integrated within Epic, some departments may utilize specialized third-party tools for specific clinical areas. These alternatives undergo rigorous vetting for efficacy and data security, adhering to all HIPAA regulations and Northwestern Medicine's stringent data governance policies. However, the integrated system offers the most comprehensive and unified approach to patient care across the enterprise.
There are no direct costs or fees passed on to physicians for utilizing Northwestern Medicine's core CDS tools. These systems are considered part of our standard clinical infrastructure and are funded centrally to support optimal patient care and operational efficiency. Any advanced features or specialized modules are typically integrated and covered under the same operational budget.
While our CDS is highly effective, limitations can include the inherent challenges of diagnostic accuracy in complex cases, particularly for very rare diseases where data may be limited. We actively work to mitigate alert fatigue through intelligent alert prioritization and customization options, and we continuously refine algorithms to improve applicability across a broader range of clinical scenarios.
Physicians can provide feedback through dedicated channels within the EHR system, as well as through their departmental leadership and our IT support teams. We have a structured process for feature requests and modifications, which involves review by clinical informatics committees to ensure alignment with evidence-based practices and overall system goals.
Northwestern Medicine provides comprehensive training through various modalities, including online modules, in-person workshops, and one-on-one support from clinical informaticists. For new updates or functionalities, targeted communications, quick guides, and refresher training sessions are regularly offered to ensure physicians can optimize their use of the CDS system.
Our CDS system is designed to incorporate the latest clinical guidelines and research through a continuous review process by our clinical informatics and medical staff committees. Updates to evidence-based recommendations are typically pushed out on a regular basis, often quarterly or as significant new evidence emerges, to ensure the most current and effective guidance is available to physicians.

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Suggest an Edit → | Last Verified: 2026-07-03 | First Added: 2026-06-21
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