This paper introduces a novel methodology for analysing and optimising the matching process between angel investors and startup companies by integrating artificial intelligence (AI) and game-theoretic models. Leveraging the natural language processing capabilities of AI engines such as Gemini and ChatGPT 4, we extract and analyse historical investment patterns to identify critical qualitative and quantitative criteria influencing investment decisions. These criteria are further refined through R programming simulations, optimising cutoff values using the Youden index to balance sensitivity and specificity in predicting successful matches. Our findings demonstrate the effectiveness of a hybrid framework that combines qualitative preferences with quantitative metrics, offering a comprehensive tool for enhancing strategic investment decisions. This study represents the first attempt to apply AI technologies systematically to the investor-startup matching process, contributing practical insights for investors, entrepreneurs, and intermediaries in navigating the early-stage investment landscape. The proposed approach not only improves matching efficiency but also supports the creation of stronger, more aligned partnerships within the entrepreneurial ecosystem.

Most medical schools teach students about illness through lectures or clinical vignettes as taught by doctors, but Boston University Chobanian & Avedisian School of Medicine offers a novel teaching experience whereby medical students share their own personal experiences with illness. 

 

Recently, the school created the Student Perspectives Initiative (SPI), a student-led program where medical students share their own personal stories with illness that match topics being taught in class. For example, a lecture on inflammatory bowel diseases in the gastroenterology module would include a presentation by a student speaking about their own experience with Crohn’s disease.

 

In a new study, students who participated in the SPI program said that it helped them learn, understand the emotions connected to the disease, and feel more connected to each other. This is the first study demonstrating that storytelling by students themselves can be a lasting and meaningful way to improve medical education.

In the field of health, the development of artificial intelligence (AI) may mean major breakthroughs in personalizing diagnoses and treatments, but there is a need to promote bias-free AI with a more diverse and inclusive vision so that everyone can benefit from it. With this study, Pompeu Fabra University (UPF), the Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) and Rovira i Virgili University (URV) have moved towards the development of medical AI applications that overcome binary logics and include the needs of trans people. The study was carried out in collaboration with the PRISMA association, which protects the rights of LGBTQIA+ people in the field of science and innovation.