Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of a medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.
- Big Data,
- Artificial intelligence,
- Cloud computing,
- Deep learning
Enthusiasm for artificial intelligence (AI) has been high for as far back as hardly any years, arriving at the top in 2018. This promotion is because of the critical advances in the field of AI and broad applications in reality . AI procedures have sent enormous waves across restorative administrations, on any occasion, fuelling a working conversation of whether AI specialists will as time goes on supersede human experts later on. At any rate, AI helps authorities by choosing good medical choices or at most supersede judgments by humans in a particular field of a general advantage like radiology. However, with the developing accessibility of general prosperity of information and the energetic improvement in the monstrous information, expressive methods have made the advancing profitable uses of this AI technology conceivable. Guided by critical clinical solicitations, essential AI strategies can open medically material data concealed in the massive extent of information, which along these lines drives effectively  . Affirmed instances of the coronavirus infection (COVID-19) surpass those with the extreme intense respiratory disorder (e.g., SARS). By correlation, SARS confirmed death case is 774 individuals in 2003. Both COVID-19 and SARS spread across landmasses, taint creatures, and people and utilize comparative mechanics to enter and contaminate the cell . On the cutting edge, a strategic reaction to COVID-19 is like that of SARS yet one significant contrast exists. In a long time since SARS, an amazing new device has been developed that might be instrumental in keeping this infection inside sensible cut-off points in particular. It is the man-made brainpower (AI). Few would contend that AI is causing a change in general health and there may be an incentive in the use of AI to the current COVID-19 episode. For instance, in anticipating the area of the following flareup . This application is successfully what the Canadian organization, Blue Dot, has endeavored to do and in that capacity was generally announced as the main association to uncover updates on the episode in late December. Different utilizations of AI that have risen in light of the most recent pandemic incorporate Benevolent AI and Imperial College London, which report that a medication affirmed for rheumatoid joint inflammation, baricitinib, may be viable against the infection. Meanwhile, Insilico Medicine situated in Hong Kong as of late declared that it’s AI calculations had planned six new atoms that could end viral replication . Because medical information continues to improve rapidly, medical data has grown quickly and huge numbers of medical devices have created an incredible risk on current hospital information systems . The field of healthcare generates a wide range of data on medical diagnosis, patient records, treatment, medication, diagnosis, etc. The real concern is that because of the limited data processing, the accuracy of certain reports has an impact on the organization of healthcare . From that issue, the data is useless without an accurate result which has been produced from the processing of the huge data. Using artificial intelligence can improve the result by employing systems that collect hundreds of actual patient information and examine it by experts and artificial intelligence tools . Big data in healthcare sectors are already applied in some hospitals, especially in the field of radiology by using advanced algorithms such as Deep Learning . Big data visualization plays an important role also not only in the management of the hospital but also in reducing the medical waste .
Typically, the artificial intelligence tool is arriving at the clinical field in present times. It is presently a reality that we should face to encourage their appearance. In this survey, we discuss various AI techniques that help in speeding up researches and assisting in the current COVID-19 crisis. Also, various learning techniques were emphasized. Cloud computing plays a vital role in virtualization since everyone is in isolation. We discuss various areas in which cloud computing can assist in concurring with this current pandemic. Consolidating enormous information and AI could prompt a significant achievement for the two patients and experts. In any case, even though we distinguished huge numbers of the main impetuses for the usage of AI in the clinical framework, the previously mentioned hindrances could likewise prevent it, particularly if the estimations of the partners are not regarded. Simulated intelligence and huge information must be incorporated and utilized in a moral way on the off chance that we need to create AI apparatuses that will be palatable for handling this pandemic. AI has been a powerful tool to distinguish early diseases due to coronavirus and helps in checking the state of tainted patients. It can essentially improve treatment consistency and dynamic by creating valuable calculations. Computer-based intelligence isn’t just useful in the treatment of COVID-19 contaminated patients yet additionally for their appropriate medical checkups. It can follow the emergency of COVID-19 at various scales, for example, clinical and epidemiological applications. It is additionally useful to encourage the exploration of this infection by utilizing examining accessible information. Simulated intelligence can help in creating appropriate treatment regimens, counteraction methodologies, and medication and immunization advancement. Be that as it may, the resulting variables of AI are viably used for describing the cerebral sickening patient and the typical patient, which were effectively grouped with 85% and 96% accuracy esteem by the planning and endorsement tests, independently. Likewise, the NLP was used to evacuate the periphery vein illness-related watchwords from clinical notes. In this way, a short time later they request the patients with periphery vein infirmity, which achieves over 91% precision. However, more future researches are to be carried out to guarantee that everybody imparts and works together in a manner that abstains from missing any basic focuses. Moral contemplations will assume a huge job by assisting us to go around potential snags in the reception of artificial intelligence instruments in helping the circumstance. Along these lines, the rest of the inquiries that despite everything destroys them, for example, the question of the sharing of duties, should be tended to. We should join a discussion among all partners worried, no matter what. In this way, it appears to be even more imperative to concentrate on quiet voices. Computerbased intelligence isn’t just useful in the treatment of COVID19, nut additionally, for their appropriate medical check-ups. Future inquiries about this can be considered to follow the emergency of COVID-19 at various scales, for example, clinical, and epidemiological situation. It will be useful to encourage the examination of this infection by utilizing dissecting the accessible information. Likewise, in creating appropriate treatment, protective procedures, medication, and immunization advancement. More experiments and surveys are to be carried out concerning the big data gathered from each patient, utilizing this data can reduce the spread or if worth saying finding a solution to this pandemic. Further work will along these lines need to address their desires with the goal that the improvement of AI is to serve patients and not despite them. The techniques put forth advances medical data with an exactness of up to 90%.
The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.
Our main services Based on Education for all Spectrum people in the world. We want to make an integration between researches and educations. We believe education is the main right of Human beings. So our services should be concentrated on inclusive education.
The KSRA team partners with local under-served communities around the world to improve the access to and quality of knowledge based on education, amplify and augment learning programs where they exist, and create new opportunities for e-learning where traditional education systems are lacking or non-existent.
FULL Paper PDF file:10.1109@ACCAI Techniques for COVID-19ESS.2020.3007939
AI Techniques for COVID-19
in IEEE Access,
PDF reference and original file: Click here
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.