Artificial intelligence (AI) is changing our way of life by allowing a computer or machine to imitate human intellect in order to solve problems. Originally, AI was created to solve simpler issues such as chess game victory, language recognition, and image retrieval, among others. AI is becoming increasingly proficient at doing what people do, but much more efficiently, quickly, and at a lower cost in addressing complex issues as technology advances.
Benjamin Gordon Palm Beach explains the AI and Covid relation
Traditional analytical and clinical decision-making methodologies in healthcare are unquestionably outclassed by AI. Machine learning (ML) algorithms, which are a subset of Artificial intelligence, can identify patterns and relationships in large huge databases and improve their precision and accuracy over time as they communicate with training examples, allowing individuals to gain novel insights into illness early recognition and classification, drug development, diagnostics, health – care procedures, treatment variance, and clinical outcomes.
AI and machine learning may have saved a few lives using COVID-19. They’ve been employed in diagnostic equipment that can read thousands of chest X-rays in less time than a radiologist. This has aided clinicians in identifying and tracking COVID cases.
Benjamin Gordon Palm Beach gives the example of Nigeria, and the technology has been implemented to help individuals assess their risk of becoming sick on a very simple but technical level. People who answer a number of questions digitally and are either given remote health assistance or referred to a hospital-based on their responses.
To identify COVID-19 disease, researchers have developed an AI image-based detection model. Scientists built a model to acquire imaging data from the lobes of the lungs automatically. The scientists investigated the data to find traits that may be used as COVID-19 predictive biomarkers.
The diagnostic biomarkers employed in the artificial intelligence model are designed to help researchers distinguish COVID-19 patients from pneumonia and healthy individuals. The model was built using 704 chest x-rays and verified using 1597 cases from various sources, including healthy, pneumonia, and COVID-19 patients. The results show that this method was effective in classifying different patient conditions.
AI Could Assist in Detecting the Next Epidemic
The AI platform BlueDot, created in Toronto, Canada, discovered an odd cluster of pneumonia in Wuhan, China, upwards of a week before the World Health Organization (WHO) issued its first alert about just a novel coronavirus. Simultaneously, the AI program Healthmap was checking social media and news sites for evidence of disease clusters at Boston Children’s Hospital, and it, too, detected the earliest signs of the COVID-19 outbreak—days before the WHO issued its first formal alarm.
These cutting-edge AI applications in healthcare show great promise for the early detection of new virus epidemics in the future. This will enable healthcare practitioners and public health officials to disseminate information more quickly, lessening the burden on health systems and, in turn, saving lives.
Well, it is not right to comment whether AI will be successful in stopping any other outbreak in the future or not. All we can do is wait and see how this evolution goes and how researchers can utilize it.
