Presenting the Global Top 100 outstanding projects: Collective Learning
This EPOS project proposes an inspiring AI-powered approach aiming to improve the coordination of collective learning and decision-making in smart cities.
Presenting the Global Top 100 outstanding projects: Mobius
Mobius offers an AI-assisted system aimed at detecting, locating and classifying whales. By conducting image analysis based on remote aerial imagery, this project can greatly assist humans in their efforts to reduce harm to wildlife.
Presenting the Global Top 100 outstanding projects: Artificial Intelligence-Based Referral System for Patients With Diabetic Retinopathy in Jalisco
This project provides an inspiring example of an AI-based referral system for patients with diabetic retinopathy. Aware of the high prevalence of diabetes and a shortage of ophthalmologists and eye illness detections services in the Mexican State of Jalisco, the founding members of this
project developed an AI model based on deep convolutional neural networks (DCNN) to enable a timelier detection of Diabetic Retinopathy in people’s eyes. The trained models preprocess and evaluate the suitability and quality and classify relevant ocular documentation with an exceptional specificity and sensitivity on local data.
Presenting the Global Top 100 outstanding projects: Climate finance accounting via artificial intelligence
After a thorough scientific, ethical, and entrepreneurial review of all projects submitted to the 2022 IRCAI Global Top 100 call, IRCAI has deemed ten submissions as “outstanding” based on their AI integrity, potential impact on the SDGs, business...
Presenting the Global Top 100 outstanding projects: MALENA
MALENA is an NLP-based ESG analyst tool enabling investors to quickly review ESG texts developed by the International Finance Corporation (IFC) to make SDG-integrated investments in emerging markets. The tool is able to identify more than 1,200 ESG risk terms, then performs a sentiment analysis to assign positive, negative or neutral sentiment to the risk terms, depending on the context.
