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Aidence

Paid

Analyzes medical images, detects diseases, saves time, improves accuracy.

5.0
HealthcareContact
Inputs: imageOutputs: text
Type
Saas
Founded
2015
Company
Aidence BV
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About Aidence

Aidence is a powerful AI-based healthcare platform, designed to simplify and streamline medical decision-making. With its cutting-edge technology, Aidence makes it easier for clinicians to navigate complex medical conditions and make more accurate diagnoses. The platform can analyze medical images and provide detailed summaries, helping to reduce the time and effort needed to reach a diagnosis. It provides clinicians with valuable insights into patient conditions, enabling them to make better decisions faster. Aidence is also able to detect and classify a wide range of diseases and conditions, helping to ensure that the right treatment is provided quickly and efficiently. Furthermore, the platform is highly secure and compliant with all relevant data protection regulations. By using Aidence, healthcare professionals can save time, improve accuracy, and ensure that patients receive the best possible care.

Key Features

Aidence quickly analyzes medical images and provides detailed summaries.
The platform can detect and classify a wide range of diseases.
It enables healthcare professionals to save time and improve accuracy.

Pros & Cons

Pros
  • Specialized AI for lung nodule management, a critical area in radiology
  • CE marked, indicating compliance with European medical device regulations
  • Acquired by RadNet and integrated into DeepHealth, suggesting strong institutional backing
  • Designed to improve diagnostic accuracy and efficiency for radiologists
  • Part of a broader health informatics platform that may offer additional capabilities
Cons
  • Currently focused primarily on lung nodule analysis; scope for other conditions should be verified
  • Pricing is not publicly listed and requires contacting the company
  • Commercial availability may vary by country; not all functionalities are available globally
  • Free tier or trial availability is not mentioned and should be verified
  • Requires integration with existing medical imaging systems, which may involve additional costs or technical setup

Best For

Aidence quickly analyzes medical images and provides detailed summaries.The platform can detect and classify a wide range of diseases.It enables healthcare professionals to save time and improve accuracy.

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FAQ

What medical conditions does Aidence's AI analyze?
Based on available information, Aidence's primary product, DeepHealth Lung (formerly Veye Lung Nodules), focuses on pulmonary nodule detection, classification, quantification, and growth assessment for lung cancer diagnosis. Other applications may exist but are not detailed in the provided content.
Is Aidence's AI platform FDA cleared or CE marked?
The website indicates that Veye Lung Nodules (now DeepHealth Lung) is CE marked in Europe. FDA clearance status is not mentioned and should be verified directly with the company.
How is Aidence's pricing structured?
The pricing model is listed as 'contact' on the directory, and no pricing details are provided on the website. Interested parties should contact DeepHealth or Aidence directly for pricing information.
Can Aidence's AI be integrated with existing hospital systems?
The platform is designed for integration into clinical workflows, but specific compatibility with PACS, RIS, or other systems should be confirmed with the vendor, as the website notes that not all functionalities are commercially available in all countries.
Is Aidence still an independent company?
No. Aidence was acquired by RadNet in 2022 and subsequently integrated into DeepHealth, a wholly owned subsidiary of RadNet. The Aidence brand may still be used for certain products, but the company is now part of DeepHealth.
What types of medical images does Aidence analyze?
Based on the product description, Aidence's AI analyzes medical images, specifically chest CT scans for lung nodule detection. The broader DeepHealth platform may support other imaging modalities, but this should be verified.