Enabling a responsive and agile performance evaluation of AI-based digital diagnostics
0Artificial intelligence (AI)-based technologies have been used successfully to support the goals of SDG3 – Ensure healthy lives and promote well-being for all at all ages – such as the use of AI-based image analysis for augmenting interpretation of X-rays for tuberculosis screening and diagnosis, increasing diagnostic accuracy in evaluation of cough and auscultation of lung sounds, etc. However, the lack of performance data on AI-based diagnostic technologies in low- and middle-income country (LMIC) settings and across a representative dataset contribute to a disorganized digital health technology landscape that may be filled with ineffective or biased AI-based diagnostic solutions. This gap not only allows for the adoption of digital health solutions that may not be suited for scale-up, but also places a time-intensive task on the end-user or individual implementing organizations of reviewing and identifying effective digital health technologies. Generating and disseminating evidence on the performance of digital diagnostic technologies based on standardized and objective assessment criteria using representative datasets can address this gap, catalyze the adoption of evidence-based digital health technologies, and subsequently lead to effective and safe use of digital health technologies among LMIC end users. This session would look at questions on performance evaluation of AI-based diagnostics while ensuring that the policy and regulatory approval timelines and requirements are in step with the pace of evolution of these technologies. \n\nSpeakers:\nRigveda Kadam\nFIND\n\nModerators:\nLuis Oala\nFraunhofer Heinrich Hertz Institute (HHI)\n\nJoin the Neural Network! \nhttps://aiforgood.itu.int/neural-network/\nThe AI for Good networking community platform powered by AI. \nDesigned to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.\n\n Watch the latest #AIforGood videos!\n\n\nExplore more #AIforGood content:\n AI for Good Top Hits\n • Top Hits \n\n AI for Good Webinars\n • AI for Good Webinars \n\n AI for Good Keynotes\n • AI for Good Keynotes \n\n Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\n Discover what's next on our programme!\nhttps://aiforgood.itu.int/programme/\n\nCheck out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nExplore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\n Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/AIforGood\nLinkedIn Page: https://www.linkedin.com/company/26511907 \nLinkedIn Group: https://www.linkedin.com/groups/8567748 \nInstagram: https://www.instagram.com/aiforgood \nFacebook: https://www.facebook.com/AIforGood\n\nWhat is AI for Good?\nWe have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.\nMore than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.\nAI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.\n\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.