Kuida PsicAnalytix: Artificial Intelligence Algorithm-Assisted Mental Health Platform for Psychodiagnostic Support and Patient Follow-Up

• Grant number: 24/06491-0
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: November 01, 2024
• End date: July 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Simone Waquim Ansarah
• Grantee: Simone Waquim Ansarah
• Company: KUIDA LTDA
• CNAE: Desenvolvimento e licenciamento de programas de computador customizáveis
• Pesquisadores principais: Giuliano Grandi
• Associated researchers: Debora Harumi Suzuki Hara ; Jean Marcos Singh Manoel ; Roberto Navarro de Mesquita ; Victor Ansarah Mancini
• Associated scholarship(s): 24/23467-6 - Development and implementation of graphical interfaces for a mental health platform, BP.TT; 24/23615-5 - Selection of Acoustic and Semantic Speech Features for Identifying Psychiatric Disorders and Training Machine Learning Algorithms, BP.TT; 24/18989-3 - Kuida PsicAnalytix: artificial intelligence algorithm-assisted mental health platform for psychodiagnostic support and patient follow-up, BP.PIPE

Abstract

Kuida is a startup founded with the aim of developing machine learning technologies for mental health. Kuida offers a corporate mental health program for healthcare institutions in group format, focusing on anxiety, depression, and burnout, and utilizes technology to assist in patient screening and clinical follow-up.Around 10% of the Brazilian population suffers from Generalized Anxiety Disorder (GAD) or Major Depressive Disorder (MDD), and about 76% of Brazilians rely on the Sistema Único de Saúde (SUS), a public health system. In 2023, over 288 thousand disability benefits were granted due to mental and behavioral disorders in Brazil, representing a high cost to the social security system. While there is a lack of access to care and excessive spending on absences, surveys suggest that the time spent by a professional in patient follow-up, namely the time used for notes and updating progress in medical records about patient monitoring and progress, is equivalent to almost 10 appointments that he could make in a period of 1 month.New solutions have emerged with the aim of addressing challenges related to mental health. Among them, the use of Artificial Intelligence (AI) in speech attribute analysis has already enabled the launch of new solutions in the market to support professionals' daily work. In the United States, approximately $70 million has been invested recently in startups developing vocal biomarkers for anxiety and depression detection, mainly in Series A rounds. Despite this growing market worldwide, the linguistic particularities of each country hinder the internationalization of these solutions.The development of a technical-scientific proof of concept of a digital telehealth platform integrated with audio transcription tools and automatic content categorization to assist in psychodiagnosis and patient follow-up is the main expected result in PIPE Phase 1. (AU)