Bio-sensored Diagnostic Kit for Detecting Tuberculosis Using Artificial Intelligence Through Neural Networks

2020 ◽  
Author(s):  
S Tamilselvi ◽  
N.M Saravana Kumar ◽  
S Lavanya ◽  
K Hariprasath ◽  
A Kavinya ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Infected Person ◽  
Medical Field ◽  
Mycobacterium Tuberculosis Infection ◽  
Major Health Problem ◽  
Major Health ◽  
Artificial Intelligent ◽  
The World ◽  
The Way

Abstract The advancement and well-developed technologies in global medical field, tuberculosis remains a major health problem. To solve the problem of tuberculosis, artificial intelligence (AI) provides the way for solving problem in real world and enlightens the world in bringing a human's brain to a machine. This paper aims to detect the presence of mycobacterium tuberculosis infection within a short span of time compared to ancient technique. It is designed in such a way that the breath of the infected person can be used to diagnose the disease at premier stage. The main objective is to design and implement a portable diagnostic kit for Tuberculosis using Neural Networks and Artificial Intelligence. The tool kit called Electronic Nose which is significant artificial intelligent component constructed through neural network contains a biosensor having an electrode coated with the galectin. The signals of hybridization on binding will be captured and processed by machine learning sensor and the output is displayed using artificial intelligence. Earlier case of diagnosis approached on the basis of grouping microorganisms days together. But this study faster to find the report in an hour. Therefore the time taken for diagnosing the presence of the bacterium can be reduced and this also paves the way for starting the treatment immediately.

scholarly journals Artificial Intelligence: A Survey on Evolution and Future Trends

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Maad M. Mijwil ◽  
Rana A. Abttan
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Power Systems ◽  
Social Networking ◽  
Social Networking Sites ◽  
Future Trends ◽  
Medical Field ◽  
Adequate Knowledge ◽  
The World

Today, the world has heard a lot about artificial intelligence (AI) and its influence in accomplishing responsibilities, and it has become famous through films, series TV and social networking sites. Artificial Intelligence (AI) is a combination of algorithms and techniques developed by developers and programmers to build metal bodies that can work for centuries with individuals. Despite the interest of everyone in this topic and its spread significantly, most people do not have adequate knowledge and understanding of this science. This science is considered as one of the essential topics in computer sciences and engineering. In this article, it has been decided to write an overview on the topic of artificial intelligence and understand how its ideas started and spread universally. In addition, there is a review of Expert Systems, Artificial Neural Networks, Fuzzy Logic, and AI applications in the medical field and power systems, especially in investigating lung images of people with COVID-19. The idea presented in this article is that the future will soon come when humans and machines will merge into cyborgs or cybernetic creatures, and they will work together when completing tasks. This idea is described as transhumanism.  

A Review of Recent Deep Learning Models in COVID-19 Diagnosis

2021 ◽  
Vol 6 (5) ◽  
pp. 10-15
Author(s):  
Ela Bhattacharya ◽  
D. Bhattacharya
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Test Results ◽  
Learning Models ◽  
Future Directions ◽  
Human Contact ◽  
The World ◽  
Short Span

COVID-19 has emerged as the latest worrisome pandemic, which is reported to have its outbreak in Wuhan, China. The infection spreads by means of human contact, as a result, it has caused massive infections across 200 countries around the world. Artificial intelligence has likewise contributed to managing the COVID-19 pandemic in various aspects within a short span of time. Deep Neural Networks that are explored in this paper have contributed to the detection of COVID-19 from imaging sources. The datasets, pre-processing, segmentation, feature extraction, classification and test results which can be useful for discovering future directions in the domain of automatic diagnosis of the disease, utilizing artificial intelligence-based frameworks, have been investigated in this paper.

The Exploration of Autonomous Vehicles

2022 ◽  
pp. 930-944
Author(s):  
Anthony J. Gephardt ◽  
Elizabeth Baoying Wang
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Intelligent Agents ◽  
Autonomous Vehicles ◽  
Learning Processes ◽  
Artificial Intelligent ◽  
The World ◽  
History Of ◽  
The Creation

This chapter explores the world of autonomous vehicles. Starting from the beginning, it covers the history of the automobile dating back to 1769. It explains how the first production automobile came about in 1885. The chapter dives into the history of auto safety, ranging from seatbelts to full-on autonomous features. One of the main focuses is the creation and implementation of artificial intelligent (AI), neural networks, intelligent agents, and deep Learning Processes. Combining the hardware on the vehicle with the intelligence of AI creates what we know as autonomous vehicles today.

Worshiping Computers

2019 ◽  
pp. 85-110
Author(s):  
Gary Smith ◽  
Jay Cordes
Keyword(s):  
Neural Networks ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Common Sense ◽  
Deep Neural Networks ◽  
Computer Software ◽  
Square Roots ◽  
The World ◽  
The Way

Computer software, particularly deep neural networks and Monte Carlo simulations, are extremely useful for the specific tasks that they have been designed to do, and they will get even better, much better. However, we should not assume that computers are smarter than us just because they can tell us the first 2000 digits of pi or show us a street map of every city in the world. One of the paradoxical things about computers is that they can excel at things that humans consider difficult (like calculating square roots) while failing at things that humans consider easy (like recognizing stop signs). They can’t pass simple tests like the Winograd Schema Challenge because they do not understand the world the way humans do. They have neither common sense nor wisdom. They are our tools, not our masters.

scholarly journals PIWI-interacting RNAs and PIWI proteins in glioma: molecular pathogenesis and role as biomarkers

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Omid Reza Tamtaji ◽  
Mohammad Behnam ◽  
Mohammad Ali Pourattar ◽  
Michael R. Hamblin ◽  
Maryam Mahjoubin-Tehran ◽  
...  
Keyword(s):  
Risk Factors ◽  
Brain Tumor ◽  
Health Problem ◽  
Molecular Mechanisms ◽  
Primary Brain Tumor ◽  
Epigenetic Mechanisms ◽  
Major Health Problem ◽  
Major Health ◽  
The World ◽  
Cellular Pathways

AbstractGlioma is the most common primary brain tumor, and is a major health problem throughout the world. Today, researchers have discovered many risk factors that are associated with the initiation and progression of gliomas. Studies have shown that PIWI-interacting RNAs (piRNAs) and PIWI proteins are involved in tumorigenesis by epigenetic mechanisms. Hence, it seems that piRNAs and PIWI proteins may be potential prognostic, diagnostic or therapeutic biomarkers in the treatment of glioma. Previous studies have demonstrated a relationship between piRNAs and PIWI proteins and some of the molecular and cellular pathways in glioma. Here, we summarize recent evidence and evaluate the molecular mechanisms by which piRNAs and PIWI proteins are involved in glioma.

scholarly journals YOLO NETWORK TRAINING FOR FACE RECOGNITION IN MEDICAL MASKS

2021 ◽  
Vol 2 (336) ◽  
pp. 125-130
Author(s):  
E. K. Temyrkanova ◽  
A. Saurambekova
Keyword(s):  
Neural Networks ◽  
Good Accuracy ◽  
Complex Task ◽  
Infected Person ◽  
Risk Of Infection ◽  
Medical Field ◽  
Facial Hair ◽  
Network Training ◽  
The Face ◽  
Recognition Systems

The detection of face masks is a very important issue for the safety and prevention of Covid-19. In the medical field, the mask reduces the potential risk of infection from an infected person, regardless of whether they have symptoms or not. Thus, the detection of masks on the face becomes a very important and complex task. The efficiency of facial recognition systems can significantly deteriorate due to occlusions, such as medical masks, hats, facial hair, and sunglasses. Currently, there are a number of different methods for recognizing objects in an image. One of the most popular methods is convolutional neural networks and their modifications. This article provides a brief description of the YOLO network, an example of training that can detect faces with a mask and without a mask, and the results of the work. The recognition model has been trained on different object recognition pre-trained models with the same data and evaluated on multiple environments to achieve good accuracy for limited identities.

scholarly journals 數位化時代社交形式和具身性概念的可能變化

2020 ◽  
Vol 18 (2) ◽  
pp. 69-73
Author(s):  
Xiaoxi WU
Keyword(s):  
Artificial Intelligence ◽  
Social Activities ◽  
Digital Commons ◽  
The World ◽  
The Way

LANGUAGE NOTE | Document text in Chinese; abstract in English only.Professor Hans-Martin Sass highlights an important aspect of the COVID-19 situation: the virus not only hurts people, but also attacks political and corporate bodies. He argues primarily on the level of basic ontology, revolving around two claims: first, that life is interconnected, and second, that long-lasting political and corporate bodies, despite their similarities to natural organisms, are more receptive to transformation and modification. In my comments, I further explore the implications of the second claim against the background of COVID-19. I focus on the concept of embodiment and show that the way embodiment figures in our interactions with others and in our experience of the world changes as more and more online social activities are organized. Most importantly, I reflect on the very meaning of embodiment in the age of high biotechnology and artificial intelligence, namely how the concept might be enlarged and/or transformed.DOWNLOAD HISTORY | This article has been downloaded 5 times in Digital Commons before migrating into this platform.

scholarly journals Complete Stenosis of the Uretero Vesical Junction in Urogenital Tuberculosis: Management and Evolution

2021 ◽  
Vol 3 (1) ◽  
pp. 21-23
Author(s):  
O. Elidrissi ◽  
M. Rkik ◽  
W. Bai ◽  
Y. Ghannam ◽  
M. Dakir ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Health Problem ◽  
Disease Type ◽  
Ureteral Stenosis ◽  
Major Health Problem ◽  
Major Health ◽  
Urogenital Tuberculosis ◽  
The World

Urogenital tuberculosis continues to be a major health problem around the world due to the epidemic of HIV infection. We report the case of a 40-year-old patient followed for urogenital tuberculosis and who presented during her follow-up a complication of her disease type ureteral stenosis, managed by endoscopic route. We try through our work to focus on the value of surveillance after anti-bacillary treatment in order to watch for complications and act in an innocuous way.

scholarly journals A Review: Artificial Intelligent Approach for Enhancing Adaptability in an Adaptive E-Learning Environment

2021 ◽  
Vol 10 (4) ◽  
pp. 37-42
Author(s):  
M.P.L. Perera
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Artificial Intelligent ◽  
Human Decision ◽  
Decision Making Processes ◽  
E Learning ◽  
Intelligent Approach ◽  
Learning Frameworks

Adaptive e-learning the aim is to fill the gap between the pupil and the educator by discussing the needs and skills of individual learners. Artificial intelligence strategies that have the potential to simulate human decision-making processes are important around adaptive e-Learning. This paper explores the Artificial techniques; Fuzzy Logic, Neural Networks, Bayesian Networks and Genetic Algorithms, highlighting their contributions to the notion of the adaptability in the sense of Adaptive E-learning. The implementation of Artificial Neural Networks to resolve problems in the current Adaptive e-learning frameworks have been established.

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