AI Driven Risk Assessment In Medicine

Machine learning is one of the most common forms of artificial intelligence in healthcare. Using machine learning models to predict the risk of post-transplant complications will improve patient care, resulting in better outcomes including survival and quality of life and paving the way for personalized medicine.

Mission

The Bold Target

Our mission is to accelerate the healthcare industry's transition to preventive and value-based care. Our philosophy revolves around enabling targeted and proactive intervention and prevention through effective early risk assessment and identification. The company is committed to pushing the boundaries of healthcare technology and disrupting traditional practices for patient care.

Getting Started

Features

Our approach embraces the most advanced technology to solve a critical problem

AI

The adoption of Artificial Intelligence (AI) has accelerated in many industries, including medicine and healthcare. AI has achieved great success in modeling complex clinical data for diagnosing and predicting treatment outcomes in cardiovascular medicine. Despite these advancements, the widespread use of AI in clinical practice for risk predictions remains limited due to the absence of a readily available platform for healthcare practitioners.

Risk Control

Advanced Heart Failure (HF) often requires life-saving treatments such as Mechanical Circulatory Support (MCS) or Heart Transplantation (HT), both of which carry high risks and costs. HT patients have a significantly higher cancer risk than the general population due to post-transplant immunosuppression to prevent organ rejection. MCS patients experience life-threatening complications such as right ventricular failure, Gastrointestinal bleeding, and stroke. Effective risk prediction and assessment guide customized treatment planning and preventive interventions to reduce risk and improve outcomes.