Health Life

AI tool gives doctors a new look at the lungs in treating COVID-19

Princeton researchers have developed a diagnostic tool that uses AI to analyze chest X-rays for COVID-19 lung damage. The tool could help doctors triage patients and better allocate scarce resources. Credit: Princeton University

Spurred by the COVID-19 pandemic, Princeton researchers have developed a diagnostic tool to analyze chest X-rays for patterns in diseased lungs. The new tool could give doctors valuable information about a patient’s condition, quickly and cheaply, at the point of care.

Jason Fleischer, professor of electrical engineering and the project’s principal investigator, said he was inspired to create the tool after reading about COVID-19’s devastating range of attacks. As hospitals have been overrun with patients, doctors have observed two basic types of lung damage, one more immediately life-threatening than the other. Treatment can differ between the types, so distinguishing the two could improve care and better allocate scarce resources.

While current differentiation methods involve expensive and time-consuming procedures, such as computed tomography (CT) scans, Fleischer’s machine learning model looks at a simple X-ray image and finds patterns that are too subtle even for the expert human eye. This tool would give doctors a new measure for determining the type and severity of COVID-19 pneumonia. And the process, on the ground, is simple.

“Importantly, there is no change in practice,” Fleischer said. “The technician doesn’t have to do anything differently. Hospitals don’t have to do any new procedure. With the X-rays they already have—and routinely take—we can give them this extra information.”

Fleischer and graduate student Mohammad Tariqul Islam posted a paper detailing their work on medrxiv (pronounced med archive), a server for scientists to share results in the form of early drafts while a paper undergoes the formal editorial process. At the time of this writing, Fleischer’s paper “Distinguishing L and H phenotypes of COVID-19 using a

Health article

Heat Stroke and Hot Cars

Since 2017, the total number of children in the US that died from heatstroke after being left in a car is 72. Most of these children are under three years of age.   

As an emergency physician practicing in Florida, I’ve seen the devastating impact of heatstroke countless times. The loss of these children’s lives is tragic but avoidable. 

Florida ranked second to Texas with 72 deaths recorded from 1998-2015. When adjusted for per capita (population per one million), Florida is the fifth-worst state in the nation.

This mind staggering research comes directly from Mr. Jan Null, CCM, of the Department of Meteorology and Climate Science at San Jose University. “This danger exists despite public education, efforts, and lobbying for laws against leaving children unattended in vehicles,” Null said.

Consider the human science: What is heatstroke? Heatstroke is defined as a condition by which the body develops hyperthermia (fever), during which the body experiences a failure of the thermoregulatory system.   

We manage heat exposure by way of the brain, circulatory system, and skin – in a way similar to a cooling system of a car.  Humans cool by ways of convection and evaporation of sweat.  Severe hyperthermia is defined as prolonged exposure to a body temperature of 104° F (40° C) or higher.  

During this syndrome, the body first develops thirst, dehydration, and perspires. As the temperature of the infant raises above 104° F, it can lead to the inability to perspire, confusion, mental agitation, and eventual coma. The body’s maximum temperature before protein starts to break down and organ failure ensues is approximately 106° F.  

Children and infants are more susceptible to heat illness due to their innate inability to regulate heat when compared to adults. The important point is that the danger is a function of not only the