 Welcome back to the ITU headquarters here in Geneva, which is, of course, hosting the AI for Good Global Summit. And here on the first day, I'm pleased to welcome here by a new guest. It's Abhishek Gupta. I hope I pronounced your name right. Yeah, you got it right. You're with AFRED. Tell me, what is AFRED and what are you doing here? So AFRED is a clinical decision aid system where we're applying deep learning principles to psychiatry. Specifically, we're starting with depression and we're looking to optimize treatment efficacy for depression. How does AI fit into that? So what we do is we ingest a lot of data on neuroimaging, on endocrinal data, metabolic data, genetic data. And what we do is we discover latent or hidden patterns from it. And we seek to personalize treatments for individuals so that they can recover faster with minimal amount of side effects. How does AI change what would just be a normal psychiatrist diagnosis? So current psychiatric practices use standard methods and questionnaires to arrive at specific diagnoses. And then there's a mapping on to different treatment plans, which they follow. But what that does is it ignores what makes us human, our uniqueness and our individuality. What we want to do is to really personalize those psychiatric treatment plans so that you don't suffer from adverse and unneeded side effects. Additionally, what happens in psychiatry is that the treatment response is really hard to predict. So let's say there's drug X and you and I take drug X. Our responses to it would be completely different. And what that means is that it would negatively affect your recovery time. So we don't want to do that and we want to really discover what would be the right treatment plan for you. Okay. Well, thanks very much. So that's Mr. Gupta from IFRED. Talk to me here about how AI can be applied to the world of psychiatry. Thank you. Cool. Thank you.