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The involvement of AI in healthcare allows triage centers to use the limited medical resources available to save as many lives as possible during a widespread public health emergency like a pandemic.
Medical triage centers attempt to save as many lives as possible by optimizing the use of limited public healthcare resources during a pandemic or other health emergencies. For example, during the initial days of the COVID-19 outbreak in Europe, Italy was one of the earliest countries to use a 'war-like' triage system to deal with its massive daily viral caseload using a priority-based approach. Following their example, Spain also used the system for bringing their then sky-high daily infections and deaths under control. There are several applications of AI in healthcare that help to reduce the workload of doctors in triage centers by bringing autonomy into specific medical operations. During a pandemic, where there is an overwhelming number of sick people in hospitals and only a limited number of doctors to tend to them, the assistance of AI in healthcare can be invaluable.
CT scans and x-rays allow doctors to understand how badly a patient's organs are affected by viral invasion or injuries. During a pandemic, AI-based x-ray tools can carry out diagnostics autonomously before classifying patients based on the severity of their health condition. Hardware-agnostic computer vision helps overwhelmed doctors with the identification of diseases such as tuberculosis, COVID-19, lung cancer, and others while performing chest radiography scans. To help with the identification, AI can detect malignancies, pneumonia, and other conditions that precede those potentially deadly ailments. Additionally, AI-based x-ray scanners can autonomously monitor the progression of the chest and abdominal lesions in patients. Based on the findings of such monitoring, AI can recommend doctors to perform surgeries or begin medicine-based therapy for such patients. Computer vision algorithms are trained by developers using thousands of datasets. Therefore, it can provide a quick and accurate diagnosis as compared to even the most accomplished medical experts.
The handling of such systems does not require doctors to have extensive medical experience. During a pandemic, when a percentage of the frontline healthcare workforce is made up of inexperienced medical students, AI-based X-ray tools are nothing short of invaluable for triage centers.
One of the most difficult choices doctors in triage centers have to make is the prioritization of patients based on their survivability chances (and their age and life expectancy). While every triage center may have its own way of classifying patients, it roughly follows a similar pattern across the globe—operating the critically ill patients who can be saved, providing painkillers and other medicines to reduce the suffering of critically ill patients who are beyond saving and provisional monitoring of mildly-ill patients who do not need intensive care. With assistance from AI-based diagnosis and predictive analysis, doctors in triage centers can classify incoming patients into one of those three categories. AI also allows healthcare experts to know exactly how many resources will be needed for each critically ill patient, so triage workers can accurately purchase medical resources when needed.
As implied earlier, medical triaging adopts a ruthless approach to save as many lives as possible during a pandemic. The inclusion of AI in healthcare centers makes it easier for doctors to make the most accurate decisions in the shortest possible amount of time.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.
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