Loading…
Infrared spectroscopy technique: An alternative technology for diabetes diagnosis
[Display omitted] Diabetes is a metabolic disorder characterized by a chronic increase in glucose caused by autoimmune destruction of the cells that produce insulin or by tissue resistance to this hormone. Although it is not a fatal disease, it can cause cardiovascular and renal complications, and r...
Saved in:
Published in: | Biomedical signal processing and control 2023-09, Vol.86, p.105246, Article 105246 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3 |
---|---|
cites | cdi_FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3 |
container_end_page | |
container_issue | |
container_start_page | 105246 |
container_title | Biomedical signal processing and control |
container_volume | 86 |
creator | Contreras-Rozo, Jose A. Mata-Miranda, Monica M. Vazquez-Zapien, Gustavo J. Delgado-Macuil, Raul J. |
description | [Display omitted]
Diabetes is a metabolic disorder characterized by a chronic increase in glucose caused by autoimmune destruction of the cells that produce insulin or by tissue resistance to this hormone. Although it is not a fatal disease, it can cause cardiovascular and renal complications, and retinopathy, among others, causing a drastic deterioration in the health of the patient. Diabetes is listed as one of the seven diseases that cause the most deaths and that affects people of any community, sex, and age. Current methods for diagnosing can be problematic because it involves taking blood samples, often causing control studies to be omitted. These methods are very invasive and many times the disease is not detected until it is advanced. For this reason, Fourier transform infrared spectroscopy has been positioned as a novel method to accurately and non-invasively detect diabetes, as well as the application of different chemometric methods to improve the accuracy of the technique. Although diverse types of samples, biomolecules, and chemometric analysis are used, there is no unified assay for its detection. Therefore, more research is needed to establish a single useful protocol that can be implemented in clinical settings. In this review, recent research on the use of this technique for the detection of diabetes using different fluids and analysis of different biomarkers is summarized together with the critical evaluation of improving the potential to improve and revolutionize how it is diagnosed, allowing a simpler, faster, and more accurate analysis. |
doi_str_mv | 10.1016/j.bspc.2023.105246 |
format | article |
fullrecord | <record><control><sourceid>elsevier_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1016_j_bspc_2023_105246</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1746809423006791</els_id><sourcerecordid>S1746809423006791</sourcerecordid><originalsourceid>FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3</originalsourceid><addsrcrecordid>eNp9kF9LwzAUxYMoOKdfwKd-gc6bP01a8WUMnYOBCPoc0uR2ZsymJnWwb29L9dWne7iHczn3R8gthQUFKu_2izp1dsGA8WFRMCHPyIwqIfOSQnn-p6ESl-QqpT2AKBUVM_K6aZtoIrosdWj7GJIN3Snr0X60_usb77Nlm5lDj7E1vT_i5IRD2J2yJsTMeVNjj2kUuzYkn67JRWMOCW9-55y8Pz2-rZ7z7ct6s1puc8sB-ty4ouJSOcUZAGcOS6ssyrICZU2h0NCCM0Vpo6RsuEIxOAiithWiksbxOWHTXTuUThEb3UX_aeJJU9AjFL3XIxQ9QtETlCH0MIVwaHb0GHWyHluLzsfhfe2C_y_-Az4nbAk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Infrared spectroscopy technique: An alternative technology for diabetes diagnosis</title><source>ScienceDirect Freedom Collection</source><creator>Contreras-Rozo, Jose A. ; Mata-Miranda, Monica M. ; Vazquez-Zapien, Gustavo J. ; Delgado-Macuil, Raul J.</creator><creatorcontrib>Contreras-Rozo, Jose A. ; Mata-Miranda, Monica M. ; Vazquez-Zapien, Gustavo J. ; Delgado-Macuil, Raul J.</creatorcontrib><description>[Display omitted]
Diabetes is a metabolic disorder characterized by a chronic increase in glucose caused by autoimmune destruction of the cells that produce insulin or by tissue resistance to this hormone. Although it is not a fatal disease, it can cause cardiovascular and renal complications, and retinopathy, among others, causing a drastic deterioration in the health of the patient. Diabetes is listed as one of the seven diseases that cause the most deaths and that affects people of any community, sex, and age. Current methods for diagnosing can be problematic because it involves taking blood samples, often causing control studies to be omitted. These methods are very invasive and many times the disease is not detected until it is advanced. For this reason, Fourier transform infrared spectroscopy has been positioned as a novel method to accurately and non-invasively detect diabetes, as well as the application of different chemometric methods to improve the accuracy of the technique. Although diverse types of samples, biomolecules, and chemometric analysis are used, there is no unified assay for its detection. Therefore, more research is needed to establish a single useful protocol that can be implemented in clinical settings. In this review, recent research on the use of this technique for the detection of diabetes using different fluids and analysis of different biomarkers is summarized together with the critical evaluation of improving the potential to improve and revolutionize how it is diagnosed, allowing a simpler, faster, and more accurate analysis.</description><identifier>ISSN: 1746-8094</identifier><identifier>EISSN: 1746-8108</identifier><identifier>DOI: 10.1016/j.bspc.2023.105246</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Artificial neural network ; Diabetes ; Fourier Transform Infrared (FTIR) spectroscopy ; Human saliva</subject><ispartof>Biomedical signal processing and control, 2023-09, Vol.86, p.105246, Article 105246</ispartof><rights>2023 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3</citedby><cites>FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27911,27912</link.rule.ids></links><search><creatorcontrib>Contreras-Rozo, Jose A.</creatorcontrib><creatorcontrib>Mata-Miranda, Monica M.</creatorcontrib><creatorcontrib>Vazquez-Zapien, Gustavo J.</creatorcontrib><creatorcontrib>Delgado-Macuil, Raul J.</creatorcontrib><title>Infrared spectroscopy technique: An alternative technology for diabetes diagnosis</title><title>Biomedical signal processing and control</title><description>[Display omitted]
Diabetes is a metabolic disorder characterized by a chronic increase in glucose caused by autoimmune destruction of the cells that produce insulin or by tissue resistance to this hormone. Although it is not a fatal disease, it can cause cardiovascular and renal complications, and retinopathy, among others, causing a drastic deterioration in the health of the patient. Diabetes is listed as one of the seven diseases that cause the most deaths and that affects people of any community, sex, and age. Current methods for diagnosing can be problematic because it involves taking blood samples, often causing control studies to be omitted. These methods are very invasive and many times the disease is not detected until it is advanced. For this reason, Fourier transform infrared spectroscopy has been positioned as a novel method to accurately and non-invasively detect diabetes, as well as the application of different chemometric methods to improve the accuracy of the technique. Although diverse types of samples, biomolecules, and chemometric analysis are used, there is no unified assay for its detection. Therefore, more research is needed to establish a single useful protocol that can be implemented in clinical settings. In this review, recent research on the use of this technique for the detection of diabetes using different fluids and analysis of different biomarkers is summarized together with the critical evaluation of improving the potential to improve and revolutionize how it is diagnosed, allowing a simpler, faster, and more accurate analysis.</description><subject>Artificial neural network</subject><subject>Diabetes</subject><subject>Fourier Transform Infrared (FTIR) spectroscopy</subject><subject>Human saliva</subject><issn>1746-8094</issn><issn>1746-8108</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kF9LwzAUxYMoOKdfwKd-gc6bP01a8WUMnYOBCPoc0uR2ZsymJnWwb29L9dWne7iHczn3R8gthQUFKu_2izp1dsGA8WFRMCHPyIwqIfOSQnn-p6ESl-QqpT2AKBUVM_K6aZtoIrosdWj7GJIN3Snr0X60_usb77Nlm5lDj7E1vT_i5IRD2J2yJsTMeVNjj2kUuzYkn67JRWMOCW9-55y8Pz2-rZ7z7ct6s1puc8sB-ty4ouJSOcUZAGcOS6ssyrICZU2h0NCCM0Vpo6RsuEIxOAiithWiksbxOWHTXTuUThEb3UX_aeJJU9AjFL3XIxQ9QtETlCH0MIVwaHb0GHWyHluLzsfhfe2C_y_-Az4nbAk</recordid><startdate>202309</startdate><enddate>202309</enddate><creator>Contreras-Rozo, Jose A.</creator><creator>Mata-Miranda, Monica M.</creator><creator>Vazquez-Zapien, Gustavo J.</creator><creator>Delgado-Macuil, Raul J.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>202309</creationdate><title>Infrared spectroscopy technique: An alternative technology for diabetes diagnosis</title><author>Contreras-Rozo, Jose A. ; Mata-Miranda, Monica M. ; Vazquez-Zapien, Gustavo J. ; Delgado-Macuil, Raul J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Artificial neural network</topic><topic>Diabetes</topic><topic>Fourier Transform Infrared (FTIR) spectroscopy</topic><topic>Human saliva</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Contreras-Rozo, Jose A.</creatorcontrib><creatorcontrib>Mata-Miranda, Monica M.</creatorcontrib><creatorcontrib>Vazquez-Zapien, Gustavo J.</creatorcontrib><creatorcontrib>Delgado-Macuil, Raul J.</creatorcontrib><collection>CrossRef</collection><jtitle>Biomedical signal processing and control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Contreras-Rozo, Jose A.</au><au>Mata-Miranda, Monica M.</au><au>Vazquez-Zapien, Gustavo J.</au><au>Delgado-Macuil, Raul J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Infrared spectroscopy technique: An alternative technology for diabetes diagnosis</atitle><jtitle>Biomedical signal processing and control</jtitle><date>2023-09</date><risdate>2023</risdate><volume>86</volume><spage>105246</spage><pages>105246-</pages><artnum>105246</artnum><issn>1746-8094</issn><eissn>1746-8108</eissn><abstract>[Display omitted]
Diabetes is a metabolic disorder characterized by a chronic increase in glucose caused by autoimmune destruction of the cells that produce insulin or by tissue resistance to this hormone. Although it is not a fatal disease, it can cause cardiovascular and renal complications, and retinopathy, among others, causing a drastic deterioration in the health of the patient. Diabetes is listed as one of the seven diseases that cause the most deaths and that affects people of any community, sex, and age. Current methods for diagnosing can be problematic because it involves taking blood samples, often causing control studies to be omitted. These methods are very invasive and many times the disease is not detected until it is advanced. For this reason, Fourier transform infrared spectroscopy has been positioned as a novel method to accurately and non-invasively detect diabetes, as well as the application of different chemometric methods to improve the accuracy of the technique. Although diverse types of samples, biomolecules, and chemometric analysis are used, there is no unified assay for its detection. Therefore, more research is needed to establish a single useful protocol that can be implemented in clinical settings. In this review, recent research on the use of this technique for the detection of diabetes using different fluids and analysis of different biomarkers is summarized together with the critical evaluation of improving the potential to improve and revolutionize how it is diagnosed, allowing a simpler, faster, and more accurate analysis.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.bspc.2023.105246</doi></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1746-8094 |
ispartof | Biomedical signal processing and control, 2023-09, Vol.86, p.105246, Article 105246 |
issn | 1746-8094 1746-8108 |
language | eng |
recordid | cdi_crossref_primary_10_1016_j_bspc_2023_105246 |
source | ScienceDirect Freedom Collection |
subjects | Artificial neural network Diabetes Fourier Transform Infrared (FTIR) spectroscopy Human saliva |
title | Infrared spectroscopy technique: An alternative technology for diabetes diagnosis |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T13%3A13%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Infrared%20spectroscopy%20technique:%20An%20alternative%20technology%20for%20diabetes%20diagnosis&rft.jtitle=Biomedical%20signal%20processing%20and%20control&rft.au=Contreras-Rozo,%20Jose%20A.&rft.date=2023-09&rft.volume=86&rft.spage=105246&rft.pages=105246-&rft.artnum=105246&rft.issn=1746-8094&rft.eissn=1746-8108&rft_id=info:doi/10.1016/j.bspc.2023.105246&rft_dat=%3Celsevier_cross%3ES1746809423006791%3C/elsevier_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c300t-ad59367d7320032de8c7ce68907ca57ea1532711f766f37e4890e04bc9ee76ad3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |