{
  "abstract": "Background: As WHO expands dolutegravir (DTG) globally, non-B HIV-1 subtypes prevalent in low- and middle-income countries (LMICs) introduce cross-resistance risks driven by natural polymorphisms. Traditional rule-based genotypic algorithms falter to resolve high-dimensional epistatic interactions, exacerbating subtype biases and threatening virologic suppression. We developed a transparent AI tool to deal with these health inequalities.\n\nMethods: Following TRIPOD+AI guidelines, we conducted a retrospective study constructing a multi-task attention network (MTL-Attention) to predict phenotypic cross-resistance to five integrase inhibitors from HIV-1 sequences. Monte Carlo Dropout was integrated to quantify epistemic uncertainty, establishing a “system deferral” mechanism. Epidemiological generalizability, along with fairness, was externally validated on a real-world cohort of 19,350 diverse sequences from the LANL database.\n\nResults: MTL-Attention achieved an AUC of 0.955 for DTG and 1.000 for cabotegravir (CAB). Decision curve analysis confirmed a positive net clinical benefit across 0% to 80%. In the LANL cohort, epistemic uncertainty variance exhibited robust cross-domain stability between B and LMIC-prevalent non-B subtypes (Mann-Whitney U test, P = 0.999). Crucially, large-scale screening identified an 11.57% cryptic phenotypic drift in DTG and an 18.65% predicted baseline resistance rate against CAB among global non-B strains.\n\nConclusions: MTL-Attention provides a low-bias solution for predicting HIV-1 phenotypic cross-resistance. When translated into a Web CDSS, it delivers a low-cost computational triage tool designed for LMICs hospitals. To advance public health, we recommend implementing this human-in-the-loop AI workflow to reduce clinical automation bias, optimize equitable allocation of high-value antiretrovirals, and strengthen worldwide surveillance systems for emerging resistant variants.\n\nKey messages: • A novel uncertainty-aware AI tool enables low-cost computational triage for HIV-1 cross-resistance, mitigating clinical automation bias and ensuring equitable patient safety in resource-limited LMICs.\n\n• Real-world deployment identified an 11.57% cryptic phenotypic drift for dolutegravir and 18.65% baseline resistance to cabotegravir among global non-B subtypes, warning public health systems.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "abstract",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "name": "MM Li"
    },
    {
      "name": "DF Yuan"
    },
    {
      "name": "YY Liu"
    },
    {
      "name": "J Zhu"
    },
    {
      "name": "SS Liu"
    },
    {
      "name": "NN Peng"
    },
    {
      "name": "XY Zhu"
    },
    {
      "name": "QJ Qian"
    },
    {
      "name": "YQ Yin"
    },
    {
      "name": "B Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/376gz913nt843.bib",
  "cited_by": 0,
  "doi": "10.1093/eurpub/ckag169.451",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13697640/",
  "id": "376gz913nt843",
  "issns": [
    "1101-1262",
    "1464-360X"
  ],
  "landing_url": "https://doi.org/10.1093/eurpub/ckag169.451",
  "language": "en",
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "3. PARALLEL PROGRAMME"
    ],
    [
      "heading",
      "AcademicSubjects/MED00860"
    ],
    [
      "heading",
      "AcademicSubjects/SOC01210"
    ],
    [
      "heading",
      "AcademicSubjects/SOC02610"
    ],
    [
      "openalex",
      "2725|HIV/AIDS drug development and treatment"
    ]
  ],
  "openalex": "W7223690225",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697640/pdf/?tool=EBI",
  "pmcid": "PMC13697640",
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/376gz913nt843.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:39Z",
      "native_id": "PMC13697640",
      "source": "pmc",
      "url": "https://doi.org/10.1093/eurpub/ckag169.451"
    },
    {
      "first_seen": "2026-10-30T12:21:44Z",
      "native_id": "PMC:PMC13697640",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13697640"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2725|HIV/AIDS drug development and treatment",
      "subfield": "infectious-disease"
    }
  ],
  "title": "Uncertainty-aware model triage for HIV-1 INSTIs phenotypic resistance in global populations",
  "title_text": "Uncertainty-aware model triage for HIV-1 INSTIs phenotypic resistance in global populations",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:34:38Z",
  "url": "https://research.draconitic.com/paper/376gz913nt843",
  "venue": "The European Journal of Public Health",
  "versions": []
}