Online ISSN: 2515-8260

Keywords : Artificial intelligence


Vatchala. S; Bingi Manorama Devi; M. Sharmila Devi; Sathish. A

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 2231-2239

Non-functional requirements play a critical role in choosing various alternative model and ultimate implementation criteria. It is extremely significant in the earlier stages of software development that requirement engineering produces successful technology and eliminates system failure. The recent work has shown that the automated extraction and classification of quality attributes from text files have been demonstrated by artificial intelligence approaches including machine learning and text mining. In the automated extraction and classification of nonfunctional specifications, we suggest a supervised categorization approach. To test our approach to obtain interesting outcomes, a very well-known dataset is used. In terms of security and performance, we obtained a specific range of 85% to 98% and obtained a best result together for security, performance and usability.


D.Raghu Raman; D. Saravanan; R. Parthiban; Dr.U. Palani; Dr.D.Stalin David; S. Usharani; D. Jayakumar

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 2531-2557

In today’s world, digitization plays an extremely prominent role in day-to-day applications.Its future deployment, needs an Internet of Things (IoT) to embrace automation, remote monitoring and predictive analysis. IoT is a device connected with an internet and it’s a combined embedded technology including actuator and sensor device. Also, it encompasses, wired and wireless communication devices, and real-world physical objects connected to the
internet. IoTis majorly used in diversified fields like smart classroom, smart banking, smart home, smart agriculture, smart healthcare application etc. Typically, IoT requires intelligence, to achieve theautomation process in an efficient way in many applications. Artificial Intelligence (AI) paves the way to makes the IoT smarter and efficient by its approaches. Due to enormous amount of data being generated in various applications, IoT combined with Machine Learning(ML) and Deep Learning(DL) models is used to enhance the functionality in complex applications. In this survey the applicationof AI, ML and DLmodels deployed in IoT are deeply explored.

Moving Towards Non-AI To AI

Nargis A Vakil; S.B. Goyal

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 2, Pages 5638-5646

A large number of researches have been conducted in the field of AI. This paper is all about the enhancements made in this popular field. Making a machine that is able to understand the background ideas of the words is very essential as it can increase the chances of better translation as well as can execute conversations as humans do. In particular, this paper states the difference between the AI and the Non-AI tasks. The work is generated for new candidates coming in the area of AI as well as some issues related to AI are also talked about.


Samyuktha P S; Geetha R V; Jayalakshmi somasundaram

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 1, Pages 697-708

Artificial Intelligence is a progressive, rapidly developing field. It has the potential to ease diagnosis, treatment and care of patients. It is vital that medical professionals are aware about Artificial Intelligence and its scope in health care. Artificial Intelligence has the capability to ease diagnosis and care. The future of medicine is Artificial Intelligence based. A survey was carried to assess the awareness levels about Artificial Intelligence and its scopes in Healthcare. A questionnaire was circulated among medical and healthcare professionals. The total participation for the study was 100. The results were collected and tabulated to be analysed using SPSS windows version 20. There was an overall positive response from the participants. 92% believed that Artificial Intelligence is the future of medicine. Recent advancements have made it imperative that the healthcare workers be aware of Artificial intelligence and its scopes. Artificial Intelligence is reaching the medical field. It is a reality that a certain level of hyperbole seems to have taken over the discussion of Artificial Intelligence in healthcare. On one hand, healthcare industrialists and researchers highlight the need for high quality health data, on the other hand, physicians are still waiting for evidence of the usefulness of these tools and wonder who will be held responsible in case of an injury due to the tool, and the other ethical factors associated with it. It can be concluded that the participants had a moderate level of knowledge about Artificial Intelligence and its scopes, which can be improved.

The Advent of Artificial Intelligence in Cardiology: The Current Applications and Future Prospects

K Prashanth; M Manjappa; C Srikar

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 1, Pages 14-20

The technology of artificial intelligence is emerging as a promising entity in cardiovascular medicine, with the potential to improve diagnosis and patient care. In this article we review the literature on artificial intelligence and its utility in cardiology. We provide a detailed description of concepts of artificial intelligence tools like machine learning, deep learning and cognitive computing. This review discusses the current evidence, applications, future prospects and limitations of artificial intelligence in cardiology.