AICOM-MP: an AI-based monkeypox detector for resource-constrained environments Article Swipe
T. Yang
,
Tianze Yang
,
Andrew Liu
,
Na An
,
Shaoshan Liu
,
Xue Liu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/09540091.2024.2306962
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/09540091.2024.2306962
Under the Autonomous Mobile Clinics (AMCs) initiative, the AI Clinics on Mobile (AICOM) project is developing, open sourcing, and standardising health AI technologies on low-end mobile devices to enable health-care access in least-developed countries (LDCs). As the first step, we introduce AICOM-MP, an AI-based monkeypox detector specially aiming for handling images taken from resource-constrained devices. We have developed AICOM-MP with the following principles: minimisation of gender, racial, and age bias; ability to conduct binary classification without over-relying on computing power; capacity to produce accurate results irrespective of images' background, resolution, and quality. AICOM-MP has achieved state-of-the-art (SOTA) performance. We have hosted AICOM-MP as a web service to allow universal access to monkeypox screening technology, and open-sourced both the source code and the dataset of AICOM-MP to allow health AI professionals to integrate AICOM-MP into their services.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/09540091.2024.2306962
- https://www.tandfonline.com/doi/pdf/10.1080/09540091.2024.2306962?needAccess=true
- OA Status
- gold
- Cited By
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391578484Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/09540091.2024.2306962Digital Object Identifier
- Title
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AICOM-MP: an AI-based monkeypox detector for resource-constrained environmentsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-02-06Full publication date if available
- Authors
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T. Yang, Tianze Yang, Andrew Liu, Na An, Shaoshan Liu, Xue LiuList of authors in order
- Landing page
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https://doi.org/10.1080/09540091.2024.2306962Publisher landing page
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https://www.tandfonline.com/doi/pdf/10.1080/09540091.2024.2306962?needAccess=trueDirect link to full text PDF
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goldOpen access status per OpenAlex
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https://www.tandfonline.com/doi/pdf/10.1080/09540091.2024.2306962?needAccess=trueDirect OA link when available
- Concepts
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Monkeypox, Computer science, Detector, Artificial intelligence, Telecommunications, Vaccinia, Chemistry, Recombinant DNA, Gene, BiochemistryTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2025: 3, 2024: 3Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.on | 10, 23, 77 |
| abstract_inverted_index.to | 27, 71, 81, 106, 110, 125, 130 |
| abstract_inverted_index.we | 39 |
| abstract_inverted_index.age | 68 |
| abstract_inverted_index.and | 18, 67, 90, 114, 120 |
| abstract_inverted_index.for | 48 |
| abstract_inverted_index.has | 93 |
| abstract_inverted_index.the | 1, 7, 36, 60, 117, 121 |
| abstract_inverted_index.web | 104 |
| abstract_inverted_index.both | 116 |
| abstract_inverted_index.code | 119 |
| abstract_inverted_index.from | 52 |
| abstract_inverted_index.have | 56, 99 |
| abstract_inverted_index.into | 133 |
| abstract_inverted_index.open | 16 |
| abstract_inverted_index.with | 59 |
| abstract_inverted_index.Under | 0 |
| abstract_inverted_index.allow | 107, 126 |
| abstract_inverted_index.bias; | 69 |
| abstract_inverted_index.first | 37 |
| abstract_inverted_index.step, | 38 |
| abstract_inverted_index.taken | 51 |
| abstract_inverted_index.their | 134 |
| abstract_inverted_index.(AMCs) | 5 |
| abstract_inverted_index.(SOTA) | 96 |
| abstract_inverted_index.Mobile | 3, 11 |
| abstract_inverted_index.access | 30, 109 |
| abstract_inverted_index.aiming | 47 |
| abstract_inverted_index.binary | 73 |
| abstract_inverted_index.enable | 28 |
| abstract_inverted_index.health | 20, 127 |
| abstract_inverted_index.hosted | 100 |
| abstract_inverted_index.images | 50 |
| abstract_inverted_index.mobile | 25 |
| abstract_inverted_index.power; | 79 |
| abstract_inverted_index.source | 118 |
| abstract_inverted_index.(AICOM) | 12 |
| abstract_inverted_index.(LDCs). | 34 |
| abstract_inverted_index.Clinics | 4, 9 |
| abstract_inverted_index.ability | 70 |
| abstract_inverted_index.conduct | 72 |
| abstract_inverted_index.dataset | 122 |
| abstract_inverted_index.devices | 26 |
| abstract_inverted_index.gender, | 65 |
| abstract_inverted_index.images' | 87 |
| abstract_inverted_index.low-end | 24 |
| abstract_inverted_index.produce | 82 |
| abstract_inverted_index.project | 13 |
| abstract_inverted_index.racial, | 66 |
| abstract_inverted_index.results | 84 |
| abstract_inverted_index.service | 105 |
| abstract_inverted_index.without | 75 |
| abstract_inverted_index.AI-based | 43 |
| abstract_inverted_index.AICOM-MP | 58, 92, 101, 124, 132 |
| abstract_inverted_index.accurate | 83 |
| abstract_inverted_index.achieved | 94 |
| abstract_inverted_index.capacity | 80 |
| abstract_inverted_index.detector | 45 |
| abstract_inverted_index.devices. | 54 |
| abstract_inverted_index.handling | 49 |
| abstract_inverted_index.quality. | 91 |
| abstract_inverted_index.AICOM-MP, | 41 |
| abstract_inverted_index.computing | 78 |
| abstract_inverted_index.countries | 33 |
| abstract_inverted_index.developed | 57 |
| abstract_inverted_index.following | 61 |
| abstract_inverted_index.integrate | 131 |
| abstract_inverted_index.introduce | 40 |
| abstract_inverted_index.monkeypox | 44, 111 |
| abstract_inverted_index.screening | 112 |
| abstract_inverted_index.services. | 135 |
| abstract_inverted_index.sourcing, | 17 |
| abstract_inverted_index.specially | 46 |
| abstract_inverted_index.universal | 108 |
| abstract_inverted_index.Autonomous | 2 |
| abstract_inverted_index.background, | 88 |
| abstract_inverted_index.developing, | 15 |
| abstract_inverted_index.health-care | 29 |
| abstract_inverted_index.initiative, | 6 |
| abstract_inverted_index.principles: | 62 |
| abstract_inverted_index.resolution, | 89 |
| abstract_inverted_index.technology, | 113 |
| abstract_inverted_index.irrespective | 85 |
| abstract_inverted_index.minimisation | 63 |
| abstract_inverted_index.open-sourced | 115 |
| abstract_inverted_index.over-relying | 76 |
| abstract_inverted_index.performance. | 97 |
| abstract_inverted_index.technologies | 22 |
| abstract_inverted_index.professionals | 129 |
| abstract_inverted_index.standardising | 19 |
| abstract_inverted_index.classification | 74 |
| abstract_inverted_index.least-developed | 32 |
| abstract_inverted_index.state-of-the-art | 95 |
| abstract_inverted_index.resource-constrained | 53 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5050739558 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.87010463 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |