Research & Articles

Lean's digital-twin solution, integrated into the Sehhaty app, creates a virtual health profile for each individual to enable personalized care, early intervention, and preventive healthcare in line with Vision 2030.

A machine learning model validated across primary healthcare centers in Saudi Arabia accurately identifies people at high risk of type 2 diabetes, enabling earlier intervention and supporting preventive healthcare.

A national study of 1,134,317 Saudi school children finds a 24.20% prevalence of tooth decay, with significant risk factors including being female, underweight, and living in the Eastern region.

Saudi Arabia's first nationwide healthcare data quality assessment introduced an automated engine to evaluate data reliability, helping improve decision-making, patient care, and the future of digital health.

This national study examines the prevalence of childhood obesity across Saudi Arabia, providing evidence to support prevention strategies, targeted interventions, and long-term public health planning.

A simulation study measuring how Saudi Arabia's non-pharmaceutical COVID-19 interventions reduced virus spread by 64%, with remote schooling the single most effective measure.

A randomized controlled trial with 12,000 vaccine-hesitant individuals shows how differently framed SMS nudges (social norms, ego, salience, loss aversion) significantly increased vaccine appointment bookings.

A custom NLP engine analyzes Sehatty app medical consultations during COVID-19, revealing utilization patterns and clinical profiles that can guide digital health decision-making in Saudi Arabia.

A machine learning model built on data from 48 Saudi Ministry of Health hospitals predicts 30-day cardiovascular readmissions, identifying 71% of cases and enabling more efficient healthcare resource use.