Review of mobile applications for optimizing the follow-up care of patients with diabetes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Nikolaos Th. Ersotelos, Andrew N. Margioris, Xu Zhang, Feng Dong

ABSTRACT

BACKGROUND: Several smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used. METHODS: Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging. RESULTS: A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance. CONCLUSIONS: The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization. More... »

PAGES

541-550

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s42000-018-0062-0

DOI

http://dx.doi.org/10.1007/s42000-018-0062-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107601516

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30317460


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aftercare", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diabetes Mellitus", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mobile Applications", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Obesity", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Bedfordshire", 
          "id": "https://www.grid.ac/institutes/grid.15034.33", 
          "name": [
            "School of Computer Science and Technology, University of Bedfordshire, University Square, Luton, LU1 3JU, Bedfordshire, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ersotelos", 
        "givenName": "Nikolaos Th.", 
        "id": "sg:person.015044570431.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015044570431.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Crete", 
          "id": "https://www.grid.ac/institutes/grid.8127.c", 
          "name": [
            "Department of Clinical Chemistry, Medical School, University of Crete, 71110, Heraklion, Crete, Greece"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Margioris", 
        "givenName": "Andrew N.", 
        "id": "sg:person.0617273153.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0617273153.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Bedfordshire", 
          "id": "https://www.grid.ac/institutes/grid.15034.33", 
          "name": [
            "School of Computer Science and Technology, University of Bedfordshire, University Square, Luton, LU1 3JU, Bedfordshire, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Xu", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Bedfordshire", 
          "id": "https://www.grid.ac/institutes/grid.15034.33", 
          "name": [
            "School of Computer Science and Technology, University of Bedfordshire, University Square, Luton, LU1 3JU, Bedfordshire, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dong", 
        "givenName": "Feng", 
        "id": "sg:person.014220301231.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014220301231.99"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.jcjd.2015.06.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013196514"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12916-015-0314-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015425112", 
          "https://doi.org/10.1186/s12916-015-0314-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12916-015-0314-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015425112", 
          "https://doi.org/10.1186/s12916-015-0314-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/dc15-0505", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018395144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diabres.2016.03.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022712396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12911-016-0356-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028230221", 
          "https://doi.org/10.1186/s12911-016-0356-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12911-016-0356-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028230221", 
          "https://doi.org/10.1186/s12911-016-0356-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/dc16-0419", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031198385"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1932296815619638", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037988713"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1932296815619638", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037988713"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/bmjdrc-2016-000264", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043431938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcjd.2016.06.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044984541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diacare.27.5.1047", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051349743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/tmj.2011.0119", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059323537"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2196/humanfactors.6029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069285332"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2196/resprot.5836", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069287377"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2196/resprot.5959", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069287396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0145721718765650", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101750022"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0145721718765650", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101750022"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "BACKGROUND: Several smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used.\nMETHODS: Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging.\nRESULTS: A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance.\nCONCLUSIONS: The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s42000-018-0062-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1030758", 
        "issn": [
          "1109-3099", 
          "2520-8721"
        ], 
        "name": "Hormones", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "17"
      }
    ], 
    "name": "Review of mobile applications for optimizing the follow-up care of patients with diabetes", 
    "pagination": "541-550", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b55ea5f4dbec7d3067b70e1c67217fcc869fa724e8e81f023b746026ee52b4b1"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30317460"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101142469"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s42000-018-0062-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107601516"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s42000-018-0062-0", 
      "https://app.dimensions.ai/details/publication/pub.1107601516"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:53", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000364_0000000364/records_72850_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs42000-018-0062-0"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s42000-018-0062-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s42000-018-0062-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s42000-018-0062-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s42000-018-0062-0'


 

This table displays all metadata directly associated to this object as RDF triples.

159 TRIPLES      21 PREDICATES      49 URIs      26 LITERALS      14 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s42000-018-0062-0 schema:about N09492e7062b64d5a8cd02e61cdf4b457
2 N657e277f3d0f4d4587706bfce2f14053
3 N9389acf0f10646b58d757f2043e6e4b4
4 Nd830e33f9dbd4085acc8e58c8fb40156
5 Nf2a3159c36a54e9383d119dd59f96fb6
6 anzsrc-for:11
7 anzsrc-for:1103
8 schema:author N6c06d92f4ce247fc9dd4c4d701852001
9 schema:citation sg:pub.10.1186/s12911-016-0356-6
10 sg:pub.10.1186/s12916-015-0314-7
11 https://doi.org/10.1016/j.diabres.2016.03.018
12 https://doi.org/10.1016/j.jcjd.2015.06.007
13 https://doi.org/10.1016/j.jcjd.2016.06.001
14 https://doi.org/10.1089/tmj.2011.0119
15 https://doi.org/10.1136/bmjdrc-2016-000264
16 https://doi.org/10.1177/0145721718765650
17 https://doi.org/10.1177/1932296815619638
18 https://doi.org/10.2196/humanfactors.6029
19 https://doi.org/10.2196/resprot.5836
20 https://doi.org/10.2196/resprot.5959
21 https://doi.org/10.2337/dc15-0505
22 https://doi.org/10.2337/dc16-0419
23 https://doi.org/10.2337/diacare.27.5.1047
24 schema:datePublished 2018-12
25 schema:datePublishedReg 2018-12-01
26 schema:description BACKGROUND: Several smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used. METHODS: Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging. RESULTS: A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance. CONCLUSIONS: The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization.
27 schema:genre research_article
28 schema:inLanguage en
29 schema:isAccessibleForFree true
30 schema:isPartOf Nb5ac9fe57fc1407db66ca17718aede43
31 Nf835b4536be845408d5e2d4f4eb0b6ef
32 sg:journal.1030758
33 schema:name Review of mobile applications for optimizing the follow-up care of patients with diabetes
34 schema:pagination 541-550
35 schema:productId N0f78df3e5dd94da9a804b86bae89abba
36 Nab93ea14e9ea49e49ac151ee0137f147
37 Nd34ba5630e664a118e0e7822e6b71c00
38 Nd60d8276023e4083809002a460b61f6f
39 Nf0cd00e043524597b09e28263662064f
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107601516
41 https://doi.org/10.1007/s42000-018-0062-0
42 schema:sdDatePublished 2019-04-11T12:53
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher Ne1099acbb4e4437aa446442f506c8502
45 schema:url https://link.springer.com/10.1007%2Fs42000-018-0062-0
46 sgo:license sg:explorer/license/
47 sgo:sdDataset articles
48 rdf:type schema:ScholarlyArticle
49 N09492e7062b64d5a8cd02e61cdf4b457 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
50 schema:name Obesity
51 rdf:type schema:DefinedTerm
52 N0f78df3e5dd94da9a804b86bae89abba schema:name dimensions_id
53 schema:value pub.1107601516
54 rdf:type schema:PropertyValue
55 N657e277f3d0f4d4587706bfce2f14053 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
56 schema:name Humans
57 rdf:type schema:DefinedTerm
58 N6c06d92f4ce247fc9dd4c4d701852001 rdf:first sg:person.015044570431.79
59 rdf:rest N914398faac3a43babb3dd434641e3804
60 N7ea517c6a93044a3a92b294c2707b779 rdf:first N9b49784f321845beac926783bcaa9d37
61 rdf:rest Ne8b578c79e3b45e883425a4a2655152c
62 N914398faac3a43babb3dd434641e3804 rdf:first sg:person.0617273153.57
63 rdf:rest N7ea517c6a93044a3a92b294c2707b779
64 N9389acf0f10646b58d757f2043e6e4b4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
65 schema:name Diabetes Mellitus
66 rdf:type schema:DefinedTerm
67 N9b49784f321845beac926783bcaa9d37 schema:affiliation https://www.grid.ac/institutes/grid.15034.33
68 schema:familyName Zhang
69 schema:givenName Xu
70 rdf:type schema:Person
71 Nab93ea14e9ea49e49ac151ee0137f147 schema:name pubmed_id
72 schema:value 30317460
73 rdf:type schema:PropertyValue
74 Nb5ac9fe57fc1407db66ca17718aede43 schema:volumeNumber 17
75 rdf:type schema:PublicationVolume
76 Nd34ba5630e664a118e0e7822e6b71c00 schema:name readcube_id
77 schema:value b55ea5f4dbec7d3067b70e1c67217fcc869fa724e8e81f023b746026ee52b4b1
78 rdf:type schema:PropertyValue
79 Nd60d8276023e4083809002a460b61f6f schema:name doi
80 schema:value 10.1007/s42000-018-0062-0
81 rdf:type schema:PropertyValue
82 Nd830e33f9dbd4085acc8e58c8fb40156 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
83 schema:name Mobile Applications
84 rdf:type schema:DefinedTerm
85 Ne1099acbb4e4437aa446442f506c8502 schema:name Springer Nature - SN SciGraph project
86 rdf:type schema:Organization
87 Ne8b578c79e3b45e883425a4a2655152c rdf:first sg:person.014220301231.99
88 rdf:rest rdf:nil
89 Nf0cd00e043524597b09e28263662064f schema:name nlm_unique_id
90 schema:value 101142469
91 rdf:type schema:PropertyValue
92 Nf2a3159c36a54e9383d119dd59f96fb6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Aftercare
94 rdf:type schema:DefinedTerm
95 Nf835b4536be845408d5e2d4f4eb0b6ef schema:issueNumber 4
96 rdf:type schema:PublicationIssue
97 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
98 schema:name Medical and Health Sciences
99 rdf:type schema:DefinedTerm
100 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
101 schema:name Clinical Sciences
102 rdf:type schema:DefinedTerm
103 sg:journal.1030758 schema:issn 1109-3099
104 2520-8721
105 schema:name Hormones
106 rdf:type schema:Periodical
107 sg:person.014220301231.99 schema:affiliation https://www.grid.ac/institutes/grid.15034.33
108 schema:familyName Dong
109 schema:givenName Feng
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014220301231.99
111 rdf:type schema:Person
112 sg:person.015044570431.79 schema:affiliation https://www.grid.ac/institutes/grid.15034.33
113 schema:familyName Ersotelos
114 schema:givenName Nikolaos Th.
115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015044570431.79
116 rdf:type schema:Person
117 sg:person.0617273153.57 schema:affiliation https://www.grid.ac/institutes/grid.8127.c
118 schema:familyName Margioris
119 schema:givenName Andrew N.
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0617273153.57
121 rdf:type schema:Person
122 sg:pub.10.1186/s12911-016-0356-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028230221
123 https://doi.org/10.1186/s12911-016-0356-6
124 rdf:type schema:CreativeWork
125 sg:pub.10.1186/s12916-015-0314-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015425112
126 https://doi.org/10.1186/s12916-015-0314-7
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.diabres.2016.03.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022712396
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.jcjd.2015.06.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013196514
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/j.jcjd.2016.06.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044984541
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1089/tmj.2011.0119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059323537
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1136/bmjdrc-2016-000264 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043431938
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1177/0145721718765650 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101750022
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1177/1932296815619638 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037988713
141 rdf:type schema:CreativeWork
142 https://doi.org/10.2196/humanfactors.6029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069285332
143 rdf:type schema:CreativeWork
144 https://doi.org/10.2196/resprot.5836 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069287377
145 rdf:type schema:CreativeWork
146 https://doi.org/10.2196/resprot.5959 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069287396
147 rdf:type schema:CreativeWork
148 https://doi.org/10.2337/dc15-0505 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018395144
149 rdf:type schema:CreativeWork
150 https://doi.org/10.2337/dc16-0419 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031198385
151 rdf:type schema:CreativeWork
152 https://doi.org/10.2337/diacare.27.5.1047 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051349743
153 rdf:type schema:CreativeWork
154 https://www.grid.ac/institutes/grid.15034.33 schema:alternateName University of Bedfordshire
155 schema:name School of Computer Science and Technology, University of Bedfordshire, University Square, Luton, LU1 3JU, Bedfordshire, UK
156 rdf:type schema:Organization
157 https://www.grid.ac/institutes/grid.8127.c schema:alternateName University of Crete
158 schema:name Department of Clinical Chemistry, Medical School, University of Crete, 71110, Heraklion, Crete, Greece
159 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...