Courtesy of Veer Sangha

In October, Veer Sangha ’23 was awarded the Elizabeth Barrett-Connor Research Award, which recognizes investigators who are being trained in epidemiology and disease prevention. 

Sangha’s novel research involved the development of an artificial intelligence technology that can diagnose heart disease, with equitable access at the forefront of his work. Simply snapping a photo of EKG results can be used in the diagnosis of a treatable disease that kills millions every year.

“As his mentor, I am thrilled that Veer’s focus and dedication to science have been recognized with this prestigious award,” wrote Rohan Khera, an assistant professor of cardiovascular medicine and health informatics. “I believe Veer’s dedication towards identifying key challenges in healthcare and working with a team to develop technological solutions to solve these problems is an essential skill needed for transforming healthcare for the better. He’s one of a kind.”

This weekend, Sangha was also named as a Rhodes Scholar. His research involves the development of a widely accessible program that can read the results of an electrocardiogram, or EKG, which is the recording of the electrical activity of a patient’s heart, and diagnose patients with left ventricular systolic dysfunction, or LVSD. 

“There is a paradigm where cardiovascular disease is often difficult to diagnose, limiting the effectiveness of available treatments, which only work if initiated in a timely manner,” Sangha said. “So our solution is to tackle disease prevention and epidemiology problems by creating affordable tools that can diagnose disease earlier.”

With age, human hearts become weaker and are able to contract less, and many develop LVSD. LVSD occurs when the left ventricle, the largest part of the heart that contracts the most blood, cannot fully contract and efficiently pump blood through a patient’s body. Patients who develop this disorder have an eightfold higher risk of heart failure and a threefold higher risk of mortality, explained Sangha. However, there are effective therapies available that can lower this risk and treat LVSD as long as patients are diagnosed early enough. 

Normally LVSD is only diagnosable using echocardiography, which involves an ultrasound of the heart that gives a clear image of the ventricles. Echoes are extremely expensive and are, therefore, inaccessible to lower income populations and more difficult to obtain in certain regions of the word. 

“In a place like India, where I was born, small rural clinics may have a medicine shelf, an EKG machine and an examination table, but physicians will not have access to an echo, which are large and costly” Sangha said. “This results in delayed or missed diagnoses. Even though effective and affordable treatments are available, there is often no way to identify the patients that need them.”

However, EKGs are widely accessible and low in cost. They are used in the diagnosis of many diseases, but rarely those that involve issues with the heart’s structure. Sangha’s research focused on finding a way to broadly use EKGs for LVSD diagnosis, eliminating the need for an echo. In turn, this would greatly increase the number of LVSD diagnoses, especially in populations that previously did not have the resources to receive an echo. 

Sangha mentioned that in recent years, colleagues at other institutions have found that it is possible to use artificial intelligence to analyze EKG data and accurately predict LVSD. However, this work involved feeding the artificial intelligence hard-to-obtain raw data directly from the EKG machine itself, which is infeasible in day to day normal care. Doctors typically analyze a standard printout of the results from the machine. Sangha’s research group focused on developing a model that could directly analyze the standard data displayed.

“We created a tool where you can take a picture, or a scan of an EKG through your phone, upload it to the model hosted on our website, and we can give you the same prediction […],” Sangha said. “The tool makes cutting-edge AI-enabled technology accessible to any patient or physician who has access to an EKG and a smartphone camera or scanner. All you have to do is take a picture. This tool is available for free.”

Sangha credits much of the possibility of him developing such technology to Khera and others he worked with alongside in the lab. The Elizabeth Barrett-Connor Research Award is typically given to advanced clinical trainees or junior faculty, so Sangha winning it as an undergraduate “is a great testament to his skill and dedication,” Khera wrote. Sangha further explained that he feels “quite fortunate to have stumbled into a group that’s as supportive and as inspiring” as the group he is in right now.

“Veer is an outstanding researcher and collaborator,” wrote Evangelos Oikonomou, a clinical fellow at YSM and a fellow member of the CarDS lab. “The quality and novelty of his work have truly surpassed all expectations. It is unheard of for an undergraduate student to compete and win one of the most prestigious Early Career Investigator Awards of the American Heart Association. Sangha has not only done that, but has remained humble through this period and has found motivation to work even harder on the next steps of his work.”

In discussing his motivations for developing a widely accessible technology, Sangha mentioned that he was born in India and moved to Missouri when he was five. Many expensive medical technologies, such as echoes, are not widely available in those regions, explained Sangha. He wanted to make sure that whatever he developed, it would be available to the populations that need it most, not just large academic centers. 

Beyond the importance of accessibility, Sangha also had a persistent desire to focus his attention on medicine. He explained that there is a history of undiagnosed disease in his family, which inspired his interest in medical research. Beginning in high school, Sangha did wet lab research, but he found his real passion in dry lab work centered around computational analysis. 

Sangha entered Yale as a statistics and biology major. However, upon taking CS50 in his first year, he discovered that he loved computer science and felt that this field of study was where he could have the greatest impact. 

“One of the things I’ve really enjoyed about the computer science curriculum at Yale is that many classes are taught in a way that inspires students to take theoretical AI concepts they learn in class, and apply them to their own areas of interest,” Sangha explained.”

Due to the COVID-19 pandemic, Sangha decided to take a gap year. While wondering where he could apply his interest in dry lab research during the pandemic, Sangha was also monitoring COVID-19 patient data as it was being released to the public. He noticed how there was a general level of confusion about how this data could best be used to improve patient outcomes. Furthermore, Sangha was receptive to the increase in the usage of digital health and technology based tools during the pandemic. This prompted him to search for work that combined patient outcomes and technology, which led him to the Yale Center for Outcomes and Evaluation. 

There he was introduced to Khera, and began working in the CarDS lab, where he has now been for the past three years. His first work with Khera’s research group was COVID-related, but it quickly shifted to LVSD diagnosis technology.

“Veer was among the first members of the Cardiovascular Data Science (CarDS) Lab at Yale, which has since grown to include 15 members across career stages,” Khera wrote. “It has been amazing to be a part of his career development and see him develop as a leader among other lab members.”

Beyond research, Sangha has spent his time at Yale involved in the Hypertension Awareness and Prevention Program at Yale. Through HAPPY, Sangha works to screen the New Haven community for their blood pressure. Sangha has also played on the club golf team throughout his time at Yale. He emphasized that while Yale has brought him wonderful research opportunities, the most important part of Yale is the people. 

“My goal for the future is to work in a research setting where I make technological innovation in healthcare as widely accessible as possible,” Sangha said. “Some of the projects that I am most excited about right now are our lab’s efforts to implement solutions in various global settings.”

Sangha was one of five students awarded the Rhodes Scholarship this weekend.