Automated Visual Evaluation (AVE)

by Clinton Health Access Initiative (CHAI) and Global Health Labs  · Based in United States → — AI-powered cervical cancer screening for low-resource settings.
Obstetrics & Gynecology Oncology Radiology

Not available publicly
Regulatory Status Disclosed

Overview

Automated Visual Evaluation (AVE) is an artificial-intelligence-based cervical screening tool developed by the Clinton Health Access Initiative (CHAI) and Global Health Labs (GHL). The tool is designed to assist healthcare providers in identifying precancerous cervical lesions using a standard smartphone.

AVE is primarily intended for clinicians, gynecologists, and community health workers operating in low- and middle-income countries (LMICs) and resource-limited care settings. It serves as an objective decision aid to augment or replace traditional, subjective Visual Inspection with Acetic Acid (VIA). The tool can be utilized either as a primary screening method or as a triage test for patients who have already screened positive for human papillomavirus (HPV).

In a clinical workflow, the provider performs a standard gynecological exam, applies acetic acid, and captures an image of the cervix using a dedicated smartphone application. The machine learning algorithm processes the image locally on the device, generating an evaluative score in less than one minute. Notable capabilities of AVE include:

  • Offline Functionality: The algorithm runs entirely on-device, requiring no active internet connectivity to analyze images.
  • Hardware Compatibility: The software is designed to run on low-cost, widely available smartphone models.
  • Objective Decision Support: It provides an immediate, automated second opinion to help reduce human subjectivity in visual assessments.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI model for precancerous cervical lesion detection
  • Utilizes smartphone images of the cervix
  • Outperforms traditional visual inspection with acetic acid (VIA)
  • Provides immediate results (within 30-60 seconds)
  • Operates offline without internet connectivity
  • Intended for use as a triage test for HPV-positive women or primary screening
  • High sensitivity (85%) and specificity (86%) for CIN2+ lesions
  • Designed for low-resource settings
  • Decision aid for health workers

Use Cases

  • Cervical cancer screening in low- and middle-income countries (LMICs)
  • Triage for women who have screened positive for HPV
  • Primary cervical cancer screening where HPV testing is unavailable
  • Augmenting the performance of Visual Inspection with Acetic Acid (VIA)

What Physicians Need to Know

Cervical Screening AI
Automated Visual Evaluation (AVE) is an AI-driven tool designed to improve cervical cancer screening, particularly in low-resource settings. It analyzes smartphone images of the cervix to detect precancerous lesions, offering a 'second opinion' to healthcare workers. AVE has shown promising results, outperforming human interpretation of cervical images and traditional cytology in accuracy. The algorithm provides a continuous score indicating the chance of precancer and can deliver results in approximately 30 seconds without internet access. It can be used for primary screening or as a triage test for HPV-positive women. Studies have indicated that AVE has a high performance in identifying cervical precancerous and cancerous lesions (CIN2+), with a sensitivity of 85% and specificity of 86%.
Physician Tip

AVE acts as a decision aid, providing a rapid 'second opinion' on cervical images. While highly accurate, the healthcare worker remains the ultimate judge of clinical management. The tool is particularly valuable in settings where access to advanced screening methods or specialized professionals is limited, as it enhances the accuracy of visual inspections. Consider its use for primary screening or as a triage for HPV-positive individuals to identify those with a high probability of precancer. Ensure proper training on image capture using smartphones, as algorithm robustness depends on the quality of processed images.

AVE is designed as a smartphone application, allowing for immediate image analysis at the point of care without internet connectivity. Future scaling efforts aim to transfer AVE to widely available and inexpensive smartphone devices. The development of a robust algorithm for smartphones requires training on images produced by various smartphone models. There is also ongoing work to design pre-applications to ensure image adequacy and post-applications to assess treatment options.

Details

Category OB/GYN AI, Oncology AI, Radiology & Imaging AI
Pricing Not available publicly
DeploymentSmartphone app
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status No AI-estimated — The developing partners are identifying pathways to secure regulatory approvals.
Integrations
EHR Not specified
Specialties Obstetrics & Gynecology, Oncology, Radiology

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Videos

Product demos, reviews, and walkthroughs for Automated Visual Evaluation (AVE).

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Frequently Asked Questions

AVE can assist in obstetrics and gynecology by providing rapid, AI-powered analysis of visual data, such as ultrasound images or colposcopic findings, to aid in early detection of abnormalities and streamline diagnostic workflows. This can potentially improve the efficiency of screening programs and support more timely interventions for conditions like cervical dysplasia or fetal anomalies.
The use of AVE in a clinical setting necessitates strict adherence to patient data privacy regulations like HIPAA and GDPR, ensuring secure handling, storage, and transmission of visual patient data. Compliance also involves validating the AVE system's accuracy and reliability for its intended clinical use, often requiring FDA clearance or CE marking for medical devices.
Established alternatives to AVE in ob/gyn include traditional manual interpretation by expert clinicians and other computer-aided detection (CAD) systems. While manual interpretation remains the gold standard, AVE aims to offer comparable accuracy with significantly improved efficiency and consistency, potentially reducing inter-observer variability and workload.
Pricing models for AVE systems can vary, often including subscription-based fees, per-use charges, or one-time licensing with ongoing maintenance costs. Many vendors offer flexible pricing structures, potentially with tiered options or pilot programs, to accommodate the budgets and needs of both larger hospital systems and smaller private practices or academic institutions.
Current limitations of AVE in obstetrics and gynecology may include the need for large, diverse datasets for training, potential biases in AI algorithms, and the inability to fully interpret nuanced clinical contexts. Efforts to address these involve developing more robust algorithms, increasing data diversity, and integrating AVE as a decision-support tool rather than a standalone diagnostic.
Data used to train AVE algorithms is typically secured through robust encryption, anonymization, and strict access controls to prevent misuse or breaches. Compliance with data protection regulations and regular security audits are also critical measures to safeguard sensitive patient information throughout the AI development and deployment lifecycle.
Vendors typically provide comprehensive training and support for physicians and their staff to effectively integrate AVE into existing workflows. This often includes initial onboarding, user manuals, online tutorials, and dedicated technical support, ensuring smooth adoption and optimal utilization of the AVE system within the practice.

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Suggest an Edit → | Last Verified: 2026-07-01 | First Added: 2026-07-01
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