Enabling safer heart
operations by revitalising
skills assessment and
surgical training regime

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AI-based System

Revolutionalising cardiac surgery care through Data Science and AI.

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Personalised Simulations

Provides realistic personalised simulations for virtual trainings to augement surgeon technique to tackle skills gap.

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Skills Assessment

Enabling personalised surgical skill assessments, performance benchmarking and identify skills gaps.

What we do

IVA-Heart computes meaningful spatioemporal statistics from operation videos using artificial intelligence algorithms comprising distance (path length), velocity, accelerations, jerk, curvature, tortuosity, turning angle, key points, motion ratio of surgical instruments, surgeon hands and surgery phases and actions. These statistics are then used to measure surgeons’ technical skill, benchmark their performance and identify skills gaps. This informs the advance video generation technology to create realistic personalised simulations for training in virtual to augment surgeon technique to tackle skills gaps.

The problem

Cardiac surgery is a major operation dedicated to treating heart diseases worldwide but it also requires advanced surgeon skills acquired through years of practice. The variation in the level of skills for each surgeon often determines surgical outocmes or postoperative mortalities and complications. It is essential that operating skills are regularly reviewed to ensure that surgeons continue to operate safely and to reduce post-operative complications and patient harm.

Current practice for reviewing surgical performance is highly subjective and time consuming. Expert surgeons review junior surgeons’ performance by either shadowing some of their operations or reviewing selected extracts of their operation recordings. This process is time consuming and highly subjective and does not ensure a comprehensive review of the surgeon’s skills and technical ability.

Our Solution

A more efficient and faster way of assessing surgeon skills is to use artificial intelligence to analyse the recordings of surgical procedures. IVA-HEART adopts this approach by employing multimodal AI to identify and track surgical instruments, tasks and hands within surgical videos. This will help created useful statistics (for example tools usage, tasks timing or motion economy) that can inform the identification of surgical mistakes, benchmarking surgeons’ performance and ranking their proficiency on a specific surgical task. These insights are presented as actionable feedback for various end-users through IVA-HEART dashboards.

In addition, latest advances in generative AI present promising opportunity for revitalising training and coaching regime through personalised simulations. IVA-HEART generates training scenarios and track surgeons performance afterwards to track surgical skills. With timely feedback and personalised trainings, surgeons will be able to improve safety in heart surgeries, leading to a reduction in the number of post-operative complications and mortality.