Collaborating Authors


Machine learning algorithm to diagnose deep vein thrombosis


A team of researchers are developing the use of an artificial intelligence (AI) algorithm with the aim of diagnosing deep vein thrombosis (DVT) more quickly and as effectively as traditional radiologist-interpreted diagnostic scans, potentially cutting down long patient waiting lists and avoiding patients unnecessarily receiving drugs to treat DVT when they don't have it. DVT is a type of blood clot most commonly formed in the leg, causing swelling, pain and discomfort--if left untreated, it can lead to fatal blood clots in the lungs. Researchers at Oxford University, Imperial College and the University of Sheffield collaborated with the tech company ThinkSono (which is led by Fouad Al-Noor and Sven Mischkewitz), to train a machine learning AI algorithm (AutoDVT) to distinguish patients who had DVT from those without DVT. The AI algorithm accurately diagnosed DVT when compared to the gold standard ultrasound scan, and the team worked out that using the algorithm could potentially save health services $150 per examination. "Traditionally, DVT diagnoses need a specialist ultrasound scan performed by a trained radiographer, and we have found that the preliminary data using the AI algorithm coupled to a hand-held ultrasound machine shows promising results," said study lead Dr. Nicola Curry, a researcher at Oxford University's Radcliffe Department of Medicine and clinician at Oxford University Hospitals NHS Foundation Trust.

Cardiovascular diseases


Are the most common cause of deaths globally, taking an estimated 17.9 million lives each year, which accounts for 31% of all deaths worldwide. Heart failure is a common event caused by Cardiovascular diseases. It is characterized by the heart's inability to pump an adequate supply of blood to the body. Without sufficient blood flow, all major body functions are disrupted. Heart failure is a condition or a collection of symptoms that weaken the heart.

Neuroscience: People subconsciously sync their heart rates with the stories they listen to

Daily Mail - Science & tech

When people listen to stories, they subconsciously synchronise their heart rates with the narrative -- and, therefore, each other -- a study has demonstrated. The finding builds on previous studies that found that people often sync up bodily functions like heartbeats or breathing when undergoing a shared experience. Experts led from the Paris Brain Institute found a similar phenomenon occurs even when people are listening to a story on their own, as long as they pay attention. The finding could help to develop a new and easy-to-administer hospital test to determine the level of a given patient's consciousness. Your heart rate is the number of times your heart beats per minute (bpm).

How artificial intelligence is helping Scots doctors prevent heart attacks


It is being used during Optical Coherence Tomography (OCT) catheterisation, which allows cardiologists to see inside the arteries of patients for more accurate placement of stents, which are used to treat blockages. When excess calcium accumulates in the blood and combines with cholesterol it forms plaque which adheres to the walls of arteries. These deposits can cause partial or complete blockage. OCT is routinely used to take images of the eyes of patients with glaucoma but is now increasingly being used to treat patients with heart disease. Dr Stuart Watkins and Dr Margaret McEntegart, consultant cardiologists at the Golden Jubilee Hospital, are now using the most advanced catheter on patients and a live recording of one of their latest cases will be used to educate cardiologists worldwide.

promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare


The first barrier is data availability. ML and deep learning models require large datasets to accurately classify or predict different tasks.27 Sectors where ML has seen immense progression are those with large datasets available to enable more complex, precise algorithms.28 In healthcare, however, the availability of data is a complex issue. On the organizational level, health data is not only expensive,27 but there is ingrained reluctance towards data sharing between hospitals as they are considered the property of each hospital to manage their individual patients.29

New Study uses DNN to Predict 99% of Coronary Heart Disease Cases


According to the World Health Organization (WHO), cardiovascular diseases (CVDs) are the leading cause of death globally, killing 17.9 million people in 2019 [1]. The WHO risk models identified many different variables as risk factors for CVDs, including the key predictor variables: age, blood pressure, body mass index, cholesterol, and tobacco use. Historically, this potpourri of factors made CVDs almost impossible to predict with any meaningful accuracy. A new study by Kondeth Fathima and E. R. Vimina [2], published in Intelligent Sustainable Systems Proceedings of ICISS 2021, used Deep Neural Networks (DNNs) with four Hidden Layers (HDs) to predict CVDs with an impressive 99% accuracy. Neural network models have come to the forefront in recent years, gaining popularity because of their exceptional prediction capabilities.

People Don't Trust AI--Here's How We Can Change That


The following essay is reprinted with permission from The Conversation, an online publication covering the latest research. Artificial intelligence can already predict the future. Police forces are using it to map when and where crime is likely to occur. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences.

A New First Responder: How Drones May Revolutionize Healthcare


A new article published last week in the European Heart Journal discusses the use of drones for delivering life-saving automated external defibrillators (AED) to out-of-hospital cardiac arrest (OHCA) patients. As the study describes, "Early treatment in line with the'chain-of-survival' concept such as cardiopulmonary resuscitation (CPR) and defibrillation by an automated external defibrillator (AED) prior to ambulance arrival is associated with increased survival. Use of AEDs in the early-cardiac-arrest electrical phase can increase survival rates to up to 50–70%. Although hundreds of thousands of AEDs are available in high-income countries, their accessibility and use are still low." Thus, the investigators of the study designed a system to deploy drones to real-life suspected OHCA patients in order to determine whether this was a viable solution to the accessibility problem.

Tech Advances Put the Annual Doctor Visit on the Critical List WSJD - Technology

"You had to decide for every single patient how you're going to provide care for them in a way you never had before," he recalls. That prompted him to ponder the role of the physical itself: "What would happen if I delayed it three months, or didn't do it at all?" For Dr. Hyman and many other physicians and their patients, the pandemic triggered a disruption in one of medicine's most common encounters--and, through virtual visits, provided an early glimpse of the physical of the future. A look at how innovation and technology are transforming the way we live, work and play. An explosion of advances in digital technology, imaging, gene sequencing and artificial intelligence will likely transform the physical into an even more virtual experience.

New artificial intelligence tech set to transform heart imaging


A team of researchers who developed the technology, including doctors at UVA Health, reports the success of the approach in a new article in the scientific journal Circulation. The team compared its AI approach, known as Virtual Native Enhancement (VNE), with contrast-enhanced CMR scans now used to monitor hypertrophic cardiomyopathy, the most common genetic heart condition. The researchers found that VNE produced higher-quality images and better captured evidence of scar in the heart, all without the need for injecting the standard contrast agent required for CMR. "This is a potentially important advance, especially if it can be expanded to other patient groups," said researcher Christopher Kramer, MD, the chief of the Division of Cardiovascular Medicine at UVA Health, Virginia's only designated Center of Excellence by the Hypertrophic Cardiomyopathy Association. "Being able to identify scar in the heart, an important contributor to progression to heart failure and sudden cardiac death, without contrast, would be highly significant. CMR scans would be done without contrast, saving cost and any risk, albeit low, from the contrast agent."