Our Research

Explore our research at the Mindful AI Lab, where technology meets a passion for public health, specifically in mental health. Our focus combines natural language processing (NLP), machine learning, and deep learning for insights into mental health and neurodevelopmental disorders. Leveraging social media platforms and electronic health records, we're developing innovative techniques for predictive modeling and identifying treatment barriers. With over a decade of experience, our team brings expertise to foster collaboration and decision-making. Join us in shaping a positive impact on public and mental health—collaborate for a brighter future.

AI-Driven ADHD Management

ADHD, a widespread condition, is currently the focus of one of our ongoing projects, where we are actively working and developing innovative solutions. This project aims to revolutionize ADHD management by leveraging cutting-edge AI techniques to analyze a wealth of information from various sources. Using natural language processing, knowledge graphs, and deep learning models, we are in the process of developing novel AI-powered tools. Additionally, we are constructing an ADHD knowledge graph that will offer a comprehensive view of the disorder and its treatments, potentially leading to technological innovations for public health conditions and the development of new interventions with fewer negative consequences.

Deep Multi-Modal Data Fusion

We are actively working on the development of a groundbreaking multi-modal data fusion approach powered by generative AI techniques. This innovative method is designed to seamlessly integrate and analyze diverse data types related to ADHD and its comorbidity, including demographics, diagnoses, and medication history. We are in the process of building and implementing this state-of-the-art generative AI-based multi-modal data fusion approach. Our dataset encompasses a total of 699,986 unique patients, including those with ADHD, control individuals, and various comorbidities, with a special emphasis on 55,000 cases of ADHD comorbidity with mental health conditions sourced from the TriNetX global health research network. This ongoing effort is poised to advance our understanding of comorbidity in ADHD and enhance its management.

Uncovering Language Disparities in Pediatric Health Records

In this project, we investigate the impact of stigmatizing language in the pediatric health records. Using innovative Natural Language Processing techniques, we analyze clinician notes to uncover racial, ethnic, and language-related disparities. Our research aims to create innovative approaches to better understand healthcare inequities. By exploring associations with clinical outcomes, we aim to inform policies and practices that promote unbiased and equitable pediatric care, advancing our mission to ensure optimal healthcare for all.

For details on both our present and past research endeavors, please visit our lab's webpage.