Queen Mary University of London


An AI tool that analyses doctor-patient conversations for early detection of mental health problems

One in three GP appointments are mental health-related; however, less than half of GP trainees undertake mental health training, and with limited time to spend with each patient and increased pressure on services, a large number of people suffering from mental illnesses, in particular those with long-term physical conditions, go undiagnosed.

We propose a tool that uses various computational methods, including natural language processing and machine learning, to analyse transcripts of conversations between GPs and patients. The aim of our tool is to help health professionals detect signs of mental health problems in their patients, leading to early diagnosis and treatment.

We are seeking collaborations with healthcare providers and clinical researchers looking to improve the quality of care and outcomes for patients experiencing mental health problems using artificial intelligence tools.

Our Team

Dr Maryam Abdollahyan is currently a Digital Fellow at Barts Health NHS Trust. Her background is in machine learning with applications in bioinformatics and health informatics.

Mohammad Bahrani is currently a PhD student at School of Electronic Engineering and Computer Science, Queen Mary University of London. His research focuses on ranking algorithms for medical information retrieval.

Cohort Two Semantica showcase stand
Cohort Two Semantica showcase stand

Apply for Cohort Four

Focusing on novel solutions that address the Future of Pain our Challenge Accelerator Programme offers a salary replacement to take six-months (full-time) away from the lab to develop a medical technology into a business venture. The programme offers entrepreneurship masterclasses, specialist advice, access to co-working space and an allowance for travel and consumables (up to £45,000).

Applications Closed