framework to detect skin disease using deep learning techniques Article Swipe
Radha Yadav
,
Saket Kumar Choudhary
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.53730/ijhs.v6ns5.10331
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.53730/ijhs.v6ns5.10331
Dermatological issues are one of the most unpreventable disorders on earth. In any case, being typical, its investigation is exceedingly problematic due to its intricacies of coloring, concealing, and handiness of hair. Recognizing skin sicknesses at the beginning phase plays a significant part in therapy. The steps which are used to dig down the problem statement and find out the solution for skin injury are finalized with the domain knowledge of the giant in that field. The analytic interaction should be exact and ideal. Because of the innovative improvements both in medication and data advancements, the achievement rates of both clinical diagnosing and clinical treatment frameworks are expanding step by step. A human-developed domain that works based on logic is utilized in the field of finding out skin illnesses with the help of AI calculations and the abuse of the immense measure of information accessible in wellbeing places and medical clinics, gathering past examinations for the specialists’ classifications is common practice in numerous works. A few frameworks have been effective in characterizing skin sicknesses and accomplishing fluctuating indicative precision. Different frameworks have depended on techniques for picture handling and component extraction that help foresee and recognize sickness types.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.53730/ijhs.v6ns5.10331
- https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226
- OA Status
- diamond
- Cited By
- 4
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4290471539
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4290471539Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.53730/ijhs.v6ns5.10331Digital Object Identifier
- Title
-
framework to detect skin disease using deep learning techniquesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-08-08Full publication date if available
- Authors
-
Radha Yadav, Saket Kumar ChoudharyList of authors in order
- Landing page
-
https://doi.org/10.53730/ijhs.v6ns5.10331Publisher landing page
- PDF URL
-
https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226Direct OA link when available
- Concepts
-
Field (mathematics), Computer science, Domain (mathematical analysis), Statement (logic), Artificial intelligence, Ideal (ethics), Data science, Mathematics, Epistemology, Mathematical analysis, Pure mathematics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
22Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4290471539 |
|---|---|
| doi | https://doi.org/10.53730/ijhs.v6ns5.10331 |
| ids.doi | https://doi.org/10.53730/ijhs.v6ns5.10331 |
| ids.openalex | https://openalex.org/W4290471539 |
| fwci | 0.59585878 |
| type | article |
| title | framework to detect skin disease using deep learning techniques |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 7270 |
| biblio.first_page | 7260 |
| topics[0].id | https://openalex.org/T10392 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.8891000151634216 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2730 |
| topics[0].subfield.display_name | Oncology |
| topics[0].display_name | Cutaneous Melanoma Detection and Management |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C9652623 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5825135111808777 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q190109 |
| concepts[0].display_name | Field (mathematics) |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.563867449760437 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C36503486 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5363181233406067 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11235244 |
| concepts[2].display_name | Domain (mathematical analysis) |
| concepts[3].id | https://openalex.org/C2777026412 |
| concepts[3].level | 2 |
| concepts[3].score | 0.4438381791114807 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2684591 |
| concepts[3].display_name | Statement (logic) |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.44323113560676575 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C2776639384 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4350472092628479 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q840396 |
| concepts[5].display_name | Ideal (ethics) |
| concepts[6].id | https://openalex.org/C2522767166 |
| concepts[6].level | 1 |
| concepts[6].score | 0.35604795813560486 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[6].display_name | Data science |
| concepts[7].id | https://openalex.org/C33923547 |
| concepts[7].level | 0 |
| concepts[7].score | 0.11375078558921814 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[7].display_name | Mathematics |
| concepts[8].id | https://openalex.org/C111472728 |
| concepts[8].level | 1 |
| concepts[8].score | 0.11272460222244263 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q9471 |
| concepts[8].display_name | Epistemology |
| concepts[9].id | https://openalex.org/C134306372 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[9].display_name | Mathematical analysis |
| concepts[10].id | https://openalex.org/C202444582 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q837863 |
| concepts[10].display_name | Pure mathematics |
| concepts[11].id | https://openalex.org/C138885662 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[11].display_name | Philosophy |
| keywords[0].id | https://openalex.org/keywords/field |
| keywords[0].score | 0.5825135111808777 |
| keywords[0].display_name | Field (mathematics) |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.563867449760437 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/domain |
| keywords[2].score | 0.5363181233406067 |
| keywords[2].display_name | Domain (mathematical analysis) |
| keywords[3].id | https://openalex.org/keywords/statement |
| keywords[3].score | 0.4438381791114807 |
| keywords[3].display_name | Statement (logic) |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.44323113560676575 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/ideal |
| keywords[5].score | 0.4350472092628479 |
| keywords[5].display_name | Ideal (ethics) |
| keywords[6].id | https://openalex.org/keywords/data-science |
| keywords[6].score | 0.35604795813560486 |
| keywords[6].display_name | Data science |
| keywords[7].id | https://openalex.org/keywords/mathematics |
| keywords[7].score | 0.11375078558921814 |
| keywords[7].display_name | Mathematics |
| keywords[8].id | https://openalex.org/keywords/epistemology |
| keywords[8].score | 0.11272460222244263 |
| keywords[8].display_name | Epistemology |
| language | en |
| locations[0].id | doi:10.53730/ijhs.v6ns5.10331 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210179027 |
| locations[0].source.issn | 2550-696X, 2550-6978 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2550-696X |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | International Journal of Health Sciences |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | International journal of health sciences |
| locations[0].landing_page_url | https://doi.org/10.53730/ijhs.v6ns5.10331 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5035412244 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5772-0266 |
| authorships[0].author.display_name | Radha Yadav |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I155125381 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Computing Science & Engineering, Galgotias University, Greater Noida, India |
| authorships[0].institutions[0].id | https://openalex.org/I155125381 |
| authorships[0].institutions[0].ror | https://ror.org/02w8ba206 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I155125381 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Galgotias University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Radha Yadav |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Computing Science & Engineering, Galgotias University, Greater Noida, India |
| authorships[1].author.id | https://openalex.org/A5042536605 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Saket Kumar Choudhary |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I155125381 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Computing Science & Engineering, Galgotias University, Greater Noida, India |
| authorships[1].institutions[0].id | https://openalex.org/I155125381 |
| authorships[1].institutions[0].ror | https://ror.org/02w8ba206 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I155125381 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Galgotias University |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Saket Kumar Choudhary |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | School of Computing Science & Engineering, Galgotias University, Greater Noida, India |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | framework to detect skin disease using deep learning techniques |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10392 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.8891000151634216 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2730 |
| primary_topic.subfield.display_name | Oncology |
| primary_topic.display_name | Cutaneous Melanoma Detection and Management |
| related_works | https://openalex.org/W1493324536, https://openalex.org/W4381987490, https://openalex.org/W2623347760, https://openalex.org/W2384445566, https://openalex.org/W1988987889, https://openalex.org/W2790866158, https://openalex.org/W3034138874, https://openalex.org/W2743342830, https://openalex.org/W2362192218, https://openalex.org/W2371931285 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.53730/ijhs.v6ns5.10331 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210179027 |
| best_oa_location.source.issn | 2550-696X, 2550-6978 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2550-696X |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | International Journal of Health Sciences |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | International journal of health sciences |
| best_oa_location.landing_page_url | https://doi.org/10.53730/ijhs.v6ns5.10331 |
| primary_location.id | doi:10.53730/ijhs.v6ns5.10331 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210179027 |
| primary_location.source.issn | 2550-696X, 2550-6978 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2550-696X |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | International Journal of Health Sciences |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | https://sciencescholar.us/journal/index.php/ijhs/article/download/10331/7226 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | International journal of health sciences |
| primary_location.landing_page_url | https://doi.org/10.53730/ijhs.v6ns5.10331 |
| publication_date | 2022-08-08 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2163605009, https://openalex.org/W2063552117, https://openalex.org/W2097117768, https://openalex.org/W2890329294, https://openalex.org/W6789046014, https://openalex.org/W1849277567, https://openalex.org/W2117539524, https://openalex.org/W3004771443, https://openalex.org/W2187178513, https://openalex.org/W4200303364, https://openalex.org/W4210790995, https://openalex.org/W2112796928, https://openalex.org/W6760385162, https://openalex.org/W2041464675, https://openalex.org/W76120228, https://openalex.org/W4250789630, https://openalex.org/W2005088335, https://openalex.org/W2565840860, https://openalex.org/W2333771190, https://openalex.org/W1529230314, https://openalex.org/W1962369832, https://openalex.org/W197962081 |
| referenced_works_count | 22 |
| abstract_inverted_index.A | 111, 164 |
| abstract_inverted_index.a | 40 |
| abstract_inverted_index.AI | 133 |
| abstract_inverted_index.In | 11 |
| abstract_inverted_index.at | 35 |
| abstract_inverted_index.be | 80 |
| abstract_inverted_index.by | 109 |
| abstract_inverted_index.in | 43, 73, 90, 121, 145, 161, 170 |
| abstract_inverted_index.is | 18, 119, 158 |
| abstract_inverted_index.of | 4, 25, 30, 70, 85, 98, 124, 132, 138, 142 |
| abstract_inverted_index.on | 9, 117, 183 |
| abstract_inverted_index.to | 22, 50 |
| abstract_inverted_index.The | 45, 76 |
| abstract_inverted_index.and | 28, 56, 82, 92, 102, 135, 148, 174, 188, 194 |
| abstract_inverted_index.any | 12 |
| abstract_inverted_index.are | 2, 48, 64, 106 |
| abstract_inverted_index.dig | 51 |
| abstract_inverted_index.due | 21 |
| abstract_inverted_index.few | 165 |
| abstract_inverted_index.for | 61, 154, 185 |
| abstract_inverted_index.its | 16, 23 |
| abstract_inverted_index.one | 3 |
| abstract_inverted_index.out | 58, 126 |
| abstract_inverted_index.the | 5, 36, 53, 59, 67, 71, 86, 95, 122, 130, 136, 139, 155 |
| abstract_inverted_index.been | 168 |
| abstract_inverted_index.both | 89, 99 |
| abstract_inverted_index.data | 93 |
| abstract_inverted_index.down | 52 |
| abstract_inverted_index.find | 57 |
| abstract_inverted_index.have | 167, 181 |
| abstract_inverted_index.help | 131, 192 |
| abstract_inverted_index.most | 6 |
| abstract_inverted_index.part | 42 |
| abstract_inverted_index.past | 152 |
| abstract_inverted_index.skin | 33, 62, 127, 172 |
| abstract_inverted_index.step | 108 |
| abstract_inverted_index.that | 74, 114, 191 |
| abstract_inverted_index.used | 49 |
| abstract_inverted_index.with | 66, 129 |
| abstract_inverted_index.abuse | 137 |
| abstract_inverted_index.based | 116 |
| abstract_inverted_index.being | 14 |
| abstract_inverted_index.case, | 13 |
| abstract_inverted_index.exact | 81 |
| abstract_inverted_index.field | 123 |
| abstract_inverted_index.giant | 72 |
| abstract_inverted_index.hair. | 31 |
| abstract_inverted_index.logic | 118 |
| abstract_inverted_index.phase | 38 |
| abstract_inverted_index.plays | 39 |
| abstract_inverted_index.rates | 97 |
| abstract_inverted_index.step. | 110 |
| abstract_inverted_index.steps | 46 |
| abstract_inverted_index.which | 47 |
| abstract_inverted_index.works | 115 |
| abstract_inverted_index.common | 159 |
| abstract_inverted_index.domain | 68, 113 |
| abstract_inverted_index.earth. | 10 |
| abstract_inverted_index.field. | 75 |
| abstract_inverted_index.ideal. | 83 |
| abstract_inverted_index.injury | 63 |
| abstract_inverted_index.issues | 1 |
| abstract_inverted_index.places | 147 |
| abstract_inverted_index.should | 79 |
| abstract_inverted_index.types. | 197 |
| abstract_inverted_index.works. | 163 |
| abstract_inverted_index.Because | 84 |
| abstract_inverted_index.finding | 125 |
| abstract_inverted_index.foresee | 193 |
| abstract_inverted_index.immense | 140 |
| abstract_inverted_index.measure | 141 |
| abstract_inverted_index.medical | 149 |
| abstract_inverted_index.picture | 186 |
| abstract_inverted_index.problem | 54 |
| abstract_inverted_index.analytic | 77 |
| abstract_inverted_index.clinical | 100, 103 |
| abstract_inverted_index.clinics, | 150 |
| abstract_inverted_index.depended | 182 |
| abstract_inverted_index.handling | 187 |
| abstract_inverted_index.numerous | 162 |
| abstract_inverted_index.practice | 160 |
| abstract_inverted_index.sickness | 196 |
| abstract_inverted_index.solution | 60 |
| abstract_inverted_index.therapy. | 44 |
| abstract_inverted_index.typical, | 15 |
| abstract_inverted_index.utilized | 120 |
| abstract_inverted_index.Different | 179 |
| abstract_inverted_index.beginning | 37 |
| abstract_inverted_index.coloring, | 26 |
| abstract_inverted_index.component | 189 |
| abstract_inverted_index.disorders | 8 |
| abstract_inverted_index.effective | 169 |
| abstract_inverted_index.expanding | 107 |
| abstract_inverted_index.finalized | 65 |
| abstract_inverted_index.gathering | 151 |
| abstract_inverted_index.handiness | 29 |
| abstract_inverted_index.illnesses | 128 |
| abstract_inverted_index.knowledge | 69 |
| abstract_inverted_index.recognize | 195 |
| abstract_inverted_index.statement | 55 |
| abstract_inverted_index.treatment | 104 |
| abstract_inverted_index.wellbeing | 146 |
| abstract_inverted_index.accessible | 144 |
| abstract_inverted_index.diagnosing | 101 |
| abstract_inverted_index.extraction | 190 |
| abstract_inverted_index.frameworks | 105, 166, 180 |
| abstract_inverted_index.indicative | 177 |
| abstract_inverted_index.innovative | 87 |
| abstract_inverted_index.medication | 91 |
| abstract_inverted_index.precision. | 178 |
| abstract_inverted_index.sicknesses | 34, 173 |
| abstract_inverted_index.techniques | 184 |
| abstract_inverted_index.Recognizing | 32 |
| abstract_inverted_index.achievement | 96 |
| abstract_inverted_index.concealing, | 27 |
| abstract_inverted_index.exceedingly | 19 |
| abstract_inverted_index.fluctuating | 176 |
| abstract_inverted_index.information | 143 |
| abstract_inverted_index.interaction | 78 |
| abstract_inverted_index.intricacies | 24 |
| abstract_inverted_index.problematic | 20 |
| abstract_inverted_index.significant | 41 |
| abstract_inverted_index.calculations | 134 |
| abstract_inverted_index.examinations | 153 |
| abstract_inverted_index.improvements | 88 |
| abstract_inverted_index.accomplishing | 175 |
| abstract_inverted_index.advancements, | 94 |
| abstract_inverted_index.investigation | 17 |
| abstract_inverted_index.unpreventable | 7 |
| abstract_inverted_index.Dermatological | 0 |
| abstract_inverted_index.characterizing | 171 |
| abstract_inverted_index.specialists’ | 156 |
| abstract_inverted_index.classifications | 157 |
| abstract_inverted_index.human-developed | 112 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.64681372 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |