The crucial role that healthcare plays in a prosperous, productive society makes it one of the most important industries in the larger big data environment. The use of AI in the healthcare industry can literally mean the difference between life and death. AI can help healthcare professionals including doctors, nurses, and others with their regular tasks. AI in healthcare can improve patient outcomes overall, improve preventative care and quality of life, and create a more precise diagnosis and treatment strategies. By examining data from the public sector, the healthcare industry, and other sources, AI can help forecast and monitor the development of contagious diseases. As a result, AI has the potential to be a key component of the global public health effort in the fight against pandemics and epidemics.
The use of machine learning (ML) algorithms and other cognitive technologies in healthcare are referred to as artificial intelligence (AI). AI can be defined simply as the ability of computers and other devices to replicate human cognition and to learn, think, and make decisions or take actions. Therefore, AI in healthcare refers to the application of machines to analyze and take action on medical data, frequently to forecast a specific outcome.
Researchers announced on Monday that a smartphone app can accurately identify Covid-19 infection in people's voices using artificial intelligence (AI). The software can be utilized in low-income nations where PCR tests are expensive and/or challenging to deliver because, according to the team, it is cheaper, quicker, and easier to use than numerous antigen testing.
According to Wafaa Aljbawi, a researcher at the Institute of Data Science at Maastricht University in the Netherlands, "the encouraging results suggest that simple voice recordings and fine-tuned AI algorithms can potentially achieve high precision in determining which patients have Covid-19 infection." Additionally, they support virtual, remote testing and have a turnaround time of under a minute. They could be utilized, for instance, at the entrances to huge gatherings to enable quick population screening, at the international congress of the European Respiratory Society in Barcelona, Spain, she added.
The upper respiratory tract and vocal cords are typically impacted by the covid-19 infection, changing a person's voice. Aljbawi and her superiors decided to look into the viability of using AI to analyze voices to identify Covid-19. They used information from the crowdsourced Covid-19 Sounds App from the University of Cambridge, which includes 893 audio samples from 4,352 healthy and unhealthy subjects, of whom 308 had tested positive for Covid-19. The researchers employed a method for analyzing voice known as Mel-spectrogram analysis, which distinguishes several voice characteristics like loudness, power, and fluctuation across time.
"We constructed various artificial intelligence models and analyzed which one worked best at classifying the Covid-19 cases," Aljbawi continued. "To distinguish the voice of Covid-19 patients from those who did not have the disease.
Long-Short Term Memory (LSTM) was one of the models that they discovered performed better than the others. Neural networks, which replicate the way the human brain functions and recognize the underlying correlations in data, are the foundation of LSTM. Its total accuracy was 89%, positive instances could be accurately detected 89% of the time, and negative cases could be correctly identified 83% of the time. Compared to cutting-edge procedures like the lateral flow test, the results of this study "suggest a considerable improvement in the accuracy of diagnosing Covid-19," stated Aljbawi. According to the researchers, substantial numbers must be used to validate their findings.
The use of ML and other cognitive disciplines for medical diagnosis is an important application of AI in healthcare. AI can assist doctors and other healthcare professionals in providing more precise diagnoses and treatment recommendations by using patient data and other information. By analyzing large data to create better preventive care suggestions for patients, AI can also assist in making healthcare more proactive and predictive.
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