Protein Engineering for Improved Health: Technological Perspectives

2019 ◽  
Vol 20 (9) ◽  
pp. 856-860 ◽  
Author(s):  
Mandeep ◽  
Rajeshwari Sinha ◽  
Pratyoosh Shukla
Keyword(s):  
Artificial Intelligence ◽  
Protein Engineering ◽  
Disease Diagnosis ◽  
Future Research ◽  
The Novel ◽  
Post Translational Modifications ◽  
Novel Proteins ◽  
The World ◽  
Health Related ◽  
Research Endeavor

Protein engineering has enabled development of novel proteins aimed at disease diagnosis, alleviation and improved health attributes. The present article provides an overview of recent approaches and techniques used to modify proteins at diverse levels, which find therapeutically relevant applications. There is immense interest among researchers to discover new and increasingly valuable solutions for various health related issues and protein engineering could be a possible venue to sort out such problems. In this mini review we have tried to decipher some of the novel aspects of protein engineering in terms of protein-based therapeutics and diagnostics, in-silico tools and related approaches. A special emphasis has been given for some innovative aspects of protein-nanoparticle conjugates; use of artificial intelligence (AI)- based tools and post-translational modifications. Utilization of such approaches in protein engineering might be ground breaking in future research endeavor of researchers across the world.

An Intelligent Disease Diagnosis System by Fuzzy Similarity Distance

2011 ◽  
Vol 71-78 ◽  
pp. 2218-2221
Author(s):  
Wen Xue Tan ◽  
Mei Sen Pan ◽  
Xiao Rong Xu
Keyword(s):  
Artificial Intelligence ◽  
Disease Diagnosis ◽  
Fuzzy Membership ◽  
The Novel ◽  
Inference Algorithm ◽  
Accuracy Rate ◽  
Diagnosis System ◽  
Fuzzy Distance ◽  
Fuzzy Similarity ◽  
Similarity Distance

The progress of Artificial intelligence and Information technology has been driving research of intelligent diagnosing, and the efficiency of diagnosis is improved by disease diagnosing system .In this paper, we analyze the comparability and relativity between fuzzy similarity distance and disease diagnosis, and initiate the theoretical model of fuzzy-distance on the basis of fuzzy membership factors vectors, and some corresponding data structure. In addition, the inference algorithm and the hierarchy of system are brought forward. Experimentation statistics demonstrate that the novel diagnosis system could obtain a satisfying accuracy rate of diagnosis, and low a rate of misdiagnosis effectively.

Reinterpreting Patent Valuation and Evaluation: The Tricky World of Nanotechnology

2011 ◽  
Vol 2 (1) ◽  
pp. 67-78
Author(s):  
Luca Escoffier
Keyword(s):  
Life Cycle ◽  
The Novel ◽  
Present Value ◽  
A Value ◽  
The World ◽  
Qualitative Variables ◽  
Innovative Idea ◽  
Health Related ◽  
Novel Method ◽  
Evaluation Techniques

In this report, the author, an IP scholar and entrepreneur, analyses how nanotechnology will pervade all industries and therefore how important it is to find a proper method to valuate and especially evaluate nanotechnology-related inventions. Attaching a value or evaluating a technology is a fundamental task nowadays, especially when innovations are supposed to be licensed or assigned. The report focuses on the different valuation and evaluation techniques professionals usually employ, and then delves into the world of nanotechnology. It tries to develop a novel method that takes environmental and health-related issues into due consideration when attaching a value or evaluating a technology in the nano world. The novel tool envisioned in the article is particularly suitable for nanotech innovations, but it can be used for the evaluation of other technologies and patents as well. The innovative idea consists of introducing the concept of Present Value After Evaluation, which takes qualitative variables into consideration and provides a figure for the analyzed technology or patent. This method and the accompanying tool are perfectly suited for evaluation purposes when environmental and human safety concerns are at stake, because they take these variables into consideration and throughout technology's life cycle.

AI EDAM at 20: Artificial intelligence in designing

2007 ◽  
Vol 21 (1) ◽  
pp. 17-18 ◽  
Author(s):  
JOHN S. GERO
Keyword(s):  
Artificial Intelligence ◽  
Engineering Design ◽  
Focal Point ◽  
Change Agents ◽  
Research Area ◽  
Design Analysis ◽  
Future Research ◽  
Archival Research ◽  
The World ◽  
Published Research

From its inception the journal Artificial Intelligence for Engineering Design, Analysis and Manufacturing recognized that designing is the precursor to analysis and manufacturing by placing it at the front of the list of areas it covers. Designing distinguishes itself from other aspects of engineering by its goal of changing the world within which it operates: designers are change agents. This characteristic makes designing a difficult task even for humans let alone for machines, because most of our knowledge and the means to acquire it assume that the world is given to us and what we need to do is characterize it. The Journal provided one of two continuing publication outlets for artificial intelligence (AI) in engineering at the time. This created the opportunity to have a focal point for the publication of archival research in the area, research that had previously appeared in disparate locations. It also offered the potential to develop a coherent research area where future research could build on previously published research.

scholarly journals Bayesian Reasoning and Artificial Intelligence against COVID-19

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Michael Gr. Voskoglou ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Artificial Intelligence ◽  
World Economy ◽  
Potential Role ◽  
Reproduction Number ◽  
Case Based Reasoning ◽  
Bayesian Reasoning ◽  
The Novel ◽  
The World ◽  
Novel Coronavirus

The article focuses on the potential role of Probability Theory and Artificial Intelligence in the battle against the pandemic of COVID-19, which, starting from China on December 2019, has created a chaos in the world economy and the lives of people, causing hundreds of thousands of deaths until now. After discussing the importance of the reproduction number Ro of the viruses, the Bayesian Probabilities are used for measuring the creditability of the diagnostic tests for the novel coronavirus. Artificial Intelligence designs are also described which are used as tools against COVID-19 and a Case-Based Reasoning expert system is proposed for the COVID-19 diagnosis.

scholarly journals A Promising and Challenging Approach: Radiologists’ Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1924
Author(s):  
Tianming Wang ◽  
Zhu Chen ◽  
Quanliang Shang ◽  
Cong Ma ◽  
Xiangyu Chen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Treatment Decision ◽  
Disease Diagnosis ◽  
Future Research ◽  
X Rays ◽  
Imaging Data ◽  
Efficacy Evaluation ◽  
Treatment Decision Making ◽  
Diagnosis And Classification

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.

A Mobile Phone-Based Expert System for Disease Diagnosis

2013 ◽  
pp. 220-235 ◽  
Author(s):  
Olufemi Moses Oyelami
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Computer Literacy ◽  
Disease Diagnosis ◽  
Machine Intelligence ◽  
Web Based ◽  
The World

Medicine is one of the areas that has benefited from the use of artificial intelligence since the advent of machine intelligence. Different expert systems for diagnosing diseases have been developed; however, they are either standalone or Web-based systems. This puts a vast majority of Africans in general and Nigerians in particular at a disadvantage, because of computer literacy, accessibility, and usage are very low in this region of the world. Recent advances in the capabilities of mobile phones and increased usage, however, have opened up new opportunities for innovative and complex applications that can be accessed via mobile phones. This chapter presents a disease diagnosis system that can be accessed via mobile phones to cater to the needs of the vast majority of users in places where healthcare is inadequate.

Visualizing Artificial Intelligence Used in Education Over Two Decades

2020 ◽  
Vol 13 (4) ◽  
pp. 32-46 ◽  
Author(s):  
Zhonggen Yu
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Betweenness Centrality ◽  
Statistics Education ◽  
Rapid Development ◽  
Interdisciplinary Cooperation ◽  
Future Research ◽  
The World ◽  
And Robotics ◽  
Cluster Mapping

With the rapid development of computer science, use of artificial intelligence (AI) in education has caught much attention across the world although it is still a young field with many under-explored research elements. Through visualizing study with bibliometric evaluation and taxonomy of the literature using both VOSviewer and CiteSpace, this study provided references for readers in terms of cluster mapping on the basis of keywords, bibliographic coupling of countries, cluster mapping on the basis of co-citations, citation counts, bursts, betweenness centrality, and sigma. Researchers could also take the findings of this study into serious consideration when they set about researching effectiveness, efficiency, or usefulness of AI in education. Future research into use of AI in education will most likely need interdisciplinary cooperation between computer science, statistics, education, cognition, and robotics.

scholarly journals A Review on Potentials of Artificial Intelligence Approaches to Forecasting COVID-19 Spreading

2021 ◽  
Author(s):  
Mohammad (Behdad) Jamshidi ◽  
Sobhan Roshani ◽  
Jakub Talla ◽  
Ali Lalbakhsh ◽  
Zdeněk Peroutka ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
World Health ◽  
Future Research ◽  
Health Issues ◽  
The World ◽  
One And Many ◽  
Health Organization ◽  
The Uk ◽  
Epidemic Diseases

Abstract COVID-19 is by now one of the deadliest public health issues that as per the last announcement of the World Health Organization up to January 21, 2021, has infected more than 108,904,983 people and claimed more than 2,398,339 lives worldwide. Although different vaccines have proved and distributed one after another, several new mutated viruses have been detected, such as the new COVID-19 variant detected in the UK. Since new variants can spread so faster than the previous one and many other strains may come, it is necessary to focus on the effective methods that are able to predict the spreading trends quickly. Regarding the considerable progress in Artificial Intelligence (AI), utilizing AI-based techniques with a concentration on Deep Learning (DL) and Machine Learning (ML), which can forecast complex trends like epidemiological issues, are proposed to conquer the problems existing in statistical or conventional techniques. In this respect, the present paper reviews the recent peer-reviewed published articles and preprint reports about solutions that could efficiently address COVID-19 spread with a focus on the state-of-the-art and AI-based methods. The results revealed that methods under discussion in this paper have had significant potentials to predict epidemic diseases like COVID-19 as well as its mutations; however, there are still weaknesses and drawbacks that fall in the domain of future research and scientific endeavors.

scholarly journals Artificial Intelligence for the Novel Corona Virus (COVID-19) Pandemic

2022 ◽  
Vol 13 (2) ◽  
pp. 1-21
Author(s):  
Ayesha Ahmed ◽  
Prabadevi Boopathy ◽  
Sudhagara Rajan S.
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Medical Diagnosis ◽  
The Novel ◽  
Economic Sectors ◽  
Future Directions ◽  
The World ◽  
Crowd Surveillance ◽  
The Impact

COVID-19 outbreak has created havoc around the world and has brought life to a disturbing halt claiming thousands of lives worldwide and infected cases rising every day. With technological advancements in Artificial Intelligence (AI), AI-based platforms can be used to deal with COVID-19 pandemic and accelerate the processes ranging from crowd surveillance to medical diagnosis. This paper renders a response to battle the virus through various AI techniques by making use of its subsets such as Machine Learning (ML), Deep learning (DL) and Natural Language Processing (NLP). A survey of promising AI methods which could be used in various applications to facilitate the processes in this pandemic along potential of AI and challenges imposed are discussed thoroughly. This paper relies on the findings of the most recent research publications and journals on COVID-19 and suggests numerous relevant strategies. A case study on the impact of COVID-19 in various economic sectors is also discussed. The potential research challenges and future directions are also presented in the paper.

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