Förbättring av provrörsbefruktning med miljöoptimering med hjälp av artificiell intelligens

Purpose and goal: ** Denna text är maskinöversatt **

The aim of EIVF-AI is to establish a system that identifies patterns and correlations between environmental elements in IVF clinics and the development of embryos. Through the integration of various sensor data and AI technologies, our ultimate goal is to improve the probability of successful pregnancies.

Expected results and effects:

Improving IVF success rates offers a significant chance to address critical global issues related to fertility, family planning, mental health, and socioeconomic equality. Advancements in IVF technology can greatly enhance quality of life for people worldwide. The urgency of this project is underscored by the European Health Sector´s oversight of worldwide IVF success rates, which currently fluctuate between 30% to 50%.

Approach and implementation: The project has been divided into five primary work packages to be completed over three years. WP0: This package focuses on knowledge dissemination and project management. WP1: In this stage, we will collect data and prepare it for the subsequent work packages. WP2: This phase is dedicated to modeling temporal dependencies in IVF procedures using Transformers.

WP3: We plan to use synthetic data for building the models in this package. WP4: This package involves developing MultiModal Learning using multiple data sources. WP5: The final package focuses on utilizing Explainable AI.