Here Are All the Latest Advances
Over the past decade, researchers have conducted an increasing number of studies exploring the applications of Artificial Intelligence in the clinical setting. Five were presented last September. But there are also many practical applications and perspectives in the covid field. Let’s take stock
Artificial intelligence can be, and in many cases already is, a powerful tool at the service of the already increased capacities of modern medicine, even when it is called upon to face events never managed before, such as the emergency due to the pandemic in progress. In West Virgina, for example, the possibility of personalizing treatments for COVID-19 patients is being studied.
But this is not the only scope, of course.
Let us then review the progress, development prospects and applications of Artificial Intelligence in the clinical setting.
The AI in Healthcare Market: The Factors That Drive Growth
According to research by Frost & Sullivan’s, the AI market in Healthcare will reach $ 6 billion in 2022, with an annual growth rate of 68%, generating savings of over $ 150 billion, while, according to Global Market Insights, the size of the Artificial Intelligence market in the healthcare sector was estimated at 1.3 billion dollars in 2018 and it is estimated that until 2025 there will be a CAGR of 41.7%.
In the medical imaging sector alone, one of the most promising among those already available and increasingly used in cardiology, pathology and ophthalmology, the AI market will record a CAGR of 30% in the forecast period 2020-2025, with a pace of dizzying growth, thanks to a number of factors, including improved computing power, learning algorithms and the availability of huge data sets, which come from health monitors and wearable medical devices.
In fact, the growing volume of health data combined with the increasing complexity of data sets, the intensification of the need to reduce the very high health costs, the improvement of computing power, the decrease of hardware costs, the growth of partnerships and inter-sectoral collaborations are among the main factors that drive market growth also to address the significant imbalance between healthcare personnel and the number of patients which often determines the need to provide health services that are not up to standard, in order to cope with the inevitability of question.
Another important driver is the adoption of AI-based technology by pharmaceutical and biotech companies around the world to accelerate the development processes of vaccines or drugs for COVID-19.
The computed tomography sector will also be affected by major innovations.
Key drivers for the growth of the computed tomography (CT) market include the increasing prevalence of various chronic lifestyle-associated diseases, such as cancer and cardiovascular conditions, and the growing demand for advanced AI-integrated imaging solutions and further investment in AI-enabled solutions are some of the factors that should drive overall market growth.
The growing demand for advanced assessment tools in the emergency department and the growing number of emergency outpatient care units are the factors that are expected to have a positive impact on the growth of the CT market, which will increase the overall demand of the AI market in the medical imaging industry.
According to the National Center for Biotechnology Information (NCBI), more than 70 million CT scans are performed in the United States and 5 million in the United Kingdom each year, with an annual rate of up to 10%. After all, the longer incubation period of COVID-19 is a huge restriction on early detection and effective treatment for the ongoing pandemic. Preliminary screening of suspected patients by CT scan can reveal early stage lung damage, with a significant impact even in developing countries, where the test / million people ratio is lower.
Artificial Intelligence and Precision Medicine
Artificial intelligence in healthcare thus qualifies as a more than decisive contribution to the so-called precision medicine, which is increasingly emerging as the medicine of the future.
For example, West Virginia University School of Medicine is using Artificial Intelligence to study how being a coal miner affects COVID-19 results and how smoking, vaporization, and having a chronic lung condition affect health. how Covid-19 patients respond to the virus.
The ability of Machine Learning to develop customized predictive models is, in itself, a precision medicine, through an innovative approach to improve patient care, which continues to attract a lot of research interest.
The use of demographics and health data associated with COVID-19 patients in West Virginia, will allow to build a machine learning model that can predict patient outcomes based on multiple variables, drawing data from the COVID-19 registry of the WVU.
The model will consider whether patients have asthma, chronic obstructive pulmonary disease, or other pulmonary conditions, evaluating CT scans of their lungs and considering whether they have chronic lung disease, smoke or use e-cigarettes, or even if they have worked in a coal mine plus other increased risk factors.
One of the innovative aspects will be that the model could help clinicians tailor care for COVID-19 patients, rather than adopting a single protocol approach.