Study Details First Artificial Intelligence Tool to Help Labs Rule-out COVID-19

Hospital-based laboratories and doctors at the front line of the COVID-19 pandemic might soon add artificial intelligence to their testing toolkit. A recent study conducted with collaborators from the University of Vermont and Cedars-Sinai describes the performance of Biocogniv's new AI-COVID™ software. The team found high accuracy in predicting the probability of COVID-19 infection using routine blood tests, which can help hospitals reduce the number of patients referred for scarce PCR testing.

"Nine months into this pandemic, we now have a better understanding of how to care for patients with COVID-19," says lead author and University of Vermont Assistant Professor Timothy Plante, M.D., M.H.S., "but there's still a big bottleneck in COVID-19 diagnosis with PCR testing."

PCR testing is the current standard diagnostic for COVID-19, and requires specific sampling, like a nasal swab, and specialized laboratory equipment to run.

Biocogniv Chief Operating Officer Tanya Kanigan, Ph.D., says, "According to data from over 100 US hospitals, the national average turnaround time for COVID-19 tests ordered in emergency rooms is above 24 hours, far from the targeted one-hour turnaround."

Complete Blood Count and Complete Metabolic Panels are common laboratory tests ordered by emergency departments and have a rapid turnaround time. These tests provide insight into the immune system, electrolytes, kidney, and liver. The researchers were able to train a model that analyzes changes in these routine tests and assigns a probability of the patient being COVID-19 negative with high accuracy.

"AI-COVID takes seconds to generate its informative result once these blood tests return, which can then be incorporated by the laboratory into its own test interpretation," says Jennifer Joe, M.D., an emergency physician in Boston, Mass. and Biocogniv's Chief Medical Officer. "In an efficient emergency department that prioritizes these routine blood tests, the door-to-result time could be under an hour."

Cedars-Sinai pulmonary and internal medicine specialist Victor Tapson, M.D., says such assistive tools that help physicians rule out possible diagnoses are familiar in emergency medicine.

"For example, a low D-dimer blood test can help us rule out clots in certain patients, allowing providers to skip expensive, often time-consuming diagnostics such as chest CT scans," says Tapson.

The Biocogniv team believes a secondary benefit of laboratories incorporating AI-COVID might be reduced time for traditional PCR results.

"With the help of AI-COVID, laboratories might relieve some of the testing bottleneck by helping providers better allocate rapid PCR testing for patients who really need it," says Joe.

The AI-COVID model was validated on real world data from Cedars-Sinai as well as on data from geographically and demographically diverse patient encounters from 22 U.S. hospitals, achieving an area under the curve (or AUC) of 0.91 out of 1.00.

"This enables the model to achieve a high sensitivity of 95% while maintaining moderate specificity of 49%, which is very similar to the performance of other commonly used rule-out tests," says Biocogniv Chief Scientific Officer George Hauser, MD, a pathologist.

Biocogniv CEO Artur Adib, Ph.D., says, "I'm honored to have such an impressive team of medical scientists from the University of Vermont and Cedars-Sinai as collaborators in validating this timely model. AI has progressed considerably; the time is now to leverage this powerful tool for new healthcare breakthroughs, and we're glad to direct it to help hospital laboratories and providers combat the current COVID-19 crisis."

Plante TB, Blau AM, Berg AN, Weinberg AS, Jun IC, Tapson VF, Kanigan TS, Adib AB.
Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.
J Med Internet Res 2020. doi: 10.2196/24048

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...