RETRACTED: Artificial intelligence for a bio-sensored detection of tuberculosis (Retracted article. See vol. 11, 2022)

被引:4
作者
Tamilselvi, S. [1 ]
Kumar, N. M. Saravana [2 ]
Lavanya, S. [3 ]
Bindhu, J. [1 ]
Kaviyavarshini, N. [4 ]
机构
[1] Bannari Amman Inst Technol, Dept Biotechnol, Erode, India
[2] M Kumarasamy Coll Engn, Dept Artificial Intelligence & Data Sci, Karur, India
[3] Sri Krishna Coll Engn & Technol, Dept Informat Technol, Coimbatore, Tamil Nadu, India
[4] Vivekanandha Coll Engn Women, Dept Informat Technol, Namakkal, India
来源
NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS | 2021年 / 10卷 / 01期
关键词
Tuberculosis; Neural networks; Artificial intelligence; Mycobacterium; Diagnosis; Galectin;
D O I
10.1007/s13721-021-00284-9
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The advancement and well-evolved technology in international clinical discipline, tuberculosis remains a major health hazard. To resolve the hassle of tuberculosis, synthetic artificial intelligence (AI) affords the manner for solving trouble in actual global and enlightens the sector in bringing a human's mind to a gadget. This paper targets to discover the presence of Mycobacterium tuberculosis infection within a brief span of time as compared to historical technique. it is designed in this type of way that the breath of the inflamed man or woman may be used to diagnose the sickness at premiere stage. The main goal is to design and implement a portable diagnostic package for Tuberculosis the use of Neural Networks and synthetic Intelligence. The device package known as digital nose that is enormous synthetic sensible element built through neural network consists of a biosensor having an electrode lined with the galectin. The indicators of hybridization on binding can be captured and processed with the aid of system gaining knowledge of sensor and the output is displayed the use of artificial intelligence. Feed-ahead back propagation neural community is used as a classifier to distinguish between inflamed or non-infected man and woman. In advance case of analysis approached on the basis of grouping microorganism's days together. However this observe quicker to find the document in an hour. Therefore, the time taken for diagnosing the presence of the bacterium may be decreased and this additionally paves the manner for starting the remedy right now with ease.
引用
收藏
页数:11
相关论文
共 22 条
[1]  
Arsand Eirik, 2010, J Diabetes Sci Technol, V4, P328
[2]  
Blonde Lawrence, 2005, Clin Cornerstone, V7 Suppl 3, pS6, DOI 10.1016/S1098-3597(05)80084-5
[3]  
Danasingh AA, 2016, Performance Analysis on Clustering Approaches for Gene Expression Data, V5, P196, DOI [10.17148/IJARCCE.2016.5242, DOI 10.17148/IJARCCE.2016.5242]
[4]   Effect of telemedicine on glycated hemoglobin in diabetes: a systematic review and meta-analysis of randomized trials [J].
Faruque, Labib Imran ;
Wiebe, Natasha ;
Ehteshami-Afshar, Arash ;
Liu, Yuanchen ;
Dianati-Maleki, Neda ;
Hemmelgarn, Brenda R. ;
Manns, Braden J. ;
Tonelli, Marcello .
CANADIAN MEDICAL ASSOCIATION JOURNAL, 2017, 189 (09) :E341-E364
[5]  
Gokilam GG, 2018, INT J ADV COMP TECHN, V5, P2074
[6]   Computerized Automated Reminder Diabetes System (CARDS): E-Mail and SMS Cell Phone Text Messaging Reminders to Support Diabetes Management [J].
Hanauer, David A. ;
Wentzell, Katherine ;
Laffel, Nikki ;
Laffel, Lori M. .
DIABETES TECHNOLOGY & THERAPEUTICS, 2009, 11 (02) :99-106
[7]   Technology and diabetes self-management: An integrative review [J].
Hunt, Caralise W. .
WORLD JOURNAL OF DIABETES, 2015, 6 (02) :225-233
[8]   Effectiveness of Digital Interventions for Improving Glycemic Control in Persons with Poorly Controlled Type 2 Diabetes: A Systematic Review, Meta-analysis, and Meta-regression Analysis [J].
Kebede, Mihiretu M. ;
Zeeb, Hajo ;
Peters, Manuela ;
Heise, Thomas L. ;
Pischke, Claudia R. .
DIABETES TECHNOLOGY & THERAPEUTICS, 2018, 20 (11) :767-782
[9]  
Kovatchev Boris, 2009, J Diabetes Sci Technol, V3, P1058
[10]   Predictive Methodology for Diabetic Data Analysis in Big Data [J].
Kumar, Saravana N. M. ;
Eswari, T. ;
Sampath, P. ;
Lavanya, S. .
BIG DATA, CLOUD AND COMPUTING CHALLENGES, 2015, 50 :203-208