doctor holding an ipad

Description

minoHealth AI is an artificial intelligence-powered clinical decision support platform developed by minoHealth AI Labs to assist healthcare professionals with medical image analysis and disease diagnosis. The platform analyses medical images, including chest X-rays and mammograms, to support the detection of conditions such as pneumonia, tuberculosis-related abnormalities, breast cancer, cardiomegaly, pleural effusion, malaria, and other infectious diseases. Users upload patient images and clinical information through the platform, after which AI-generated diagnostic results are produced to support clinical assessment.

Beyond clinical diagnostics, minoHealth AI Labs conducts research and development in biomedical fields including oncology, neuroscience, biotechnology, regenerative medicine, epidemiology, and nutrition. The platform is designed to improve access to timely and affordable diagnostic support, particularly in settings with limited access to specialist radiologists.

minoHealth collaborates with healthcare institutions, research organisations, and international partners to develop and evaluate AI systems for healthcare applications, while continuing to test and refine its diagnostic models before broader deployment.

Objective

  • Support AI-assisted diagnosis from medical images.
  • Improve access to timely and affordable diagnostic services.
  • Assist healthcare professionals in detecting radiological and infectious diseases.
  • Advance AI research in healthcare and biomedical sciences.
  • Strengthen healthcare delivery through AI-powered clinical decision support.

Risk Classification

minoHealth AI has been assigned a High Risk classification because it provides AI-generated diagnostic support in healthcare, where outputs may directly influence clinical assessments and patient care. Inaccurate or incomplete diagnostic results could affect medical decision-making, treatment planning, or patient outcomes if relied upon without appropriate clinical review. Key considerations include: 1. Accuracy and reliability of AI-generated diagnostic results. 2. Protection of sensitive patient health and medical imaging data. 3. Transparency and explainability of AI recommendations. 4. Human oversight by qualified healthcare professionals. 5. Cybersecurity and governance of clinical data.

Risk tier: High

  • Visibility

    Public

  • Linked Institution

    Ministry of Health and Ga West Municipal Hospital

  • Organization type

    Private Sector

  • Sector

    Health Technology (HealthTech)

  • Specific sectors

    Healthcare

  • Risk Tier

    High

  • SDG goal

    3 and 9

  • Deployment status

    in use

  • Coverage area

    Ghana, with research collaborations and healthcare initiatives extending across Africa and internationally.

  • Uses personal data?

    Yes