{
  "abstract": "Fever in the returning traveller is a challenging presentation that requires a wide array of clinical expertise and draws on complex medical decision-making. Recent advancements in artificial intelligence have shown it can be a helpful clinical support tool in this context. This scoping review, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines and registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/BSPKX), aimed to identify the current state of artificial intelligence use in assessing fever in the returning traveller. Here we describe the three eligible studies evaluating three distinct AI approaches identified in the literature. These heterogenous studies reported promising performance on study-specific endpoints in controlled settings. Given the lack of external validation, narrow populations studied, and absence of real-world implementation or user acceptance testing, further research is needed to explore this technology in a real-world clinical setting. The limited available evidence suggests that AI may have future potential to support assessment of fever in the returning traveller; however, clinical utility, safety, and real-world effectiveness remain unestablished. Large language models represent an emerging area of interest but were not evaluated in the studies included in this review. Author summary: We wanted to understand how artificial intelligence has been used to help clinicians assess fever in people who become ill after international travel. This clinical problem is difficult because the list of possible infections is broad and depends on travel destination, exposure history, symptoms, and test results. We reviewed the published literature and found three eligible studies. These studies described different approaches: a rule-based expert system to generate a ranked list of possible diagnoses, a machine-learning model to predict malaria risk, and a model using immune markers to help distinguish between infections. All three studies suggested that artificial intelligence could support clinical assessment in controlled settings. We also found that all studies were conducted in hospital-based populations. None of the included studies reported real-world clinical implementation or user acceptability testing, and external validation was limited. We believe this review shows that artificial intelligence is a promising but early area in travel-related fever assessment. More research, including external validation and real-world implementation studies, is needed before these tools can be confidently adopted in routine clinical care.",
  "abstract_shown": true,
  "affiliations": [
    "Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada",
    "Division of General Internal Medicine, Michael G. DeGroote School of Medicine, McMaster University Medical Center, Hamilton, Ontario, Canada",
    "Division of Infectious Diseases, Michael G. DeGroote School of Medicine, McMaster University Medical Center, Hamilton, Ontario, Canada"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
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        0
      ],
      "name": "Bhavya Gandhi"
    },
    {
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        1
      ],
      "name": "Leo Morjaria"
    },
    {
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        2
      ],
      "name": "Imeth Illamperuma"
    },
    {
      "name": "Meha Bhatt"
    },
    {
      "name": "Andrew Kapoor"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/anhmr6r5zaspz.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pdig.0001742",
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    "2767-3170"
  ],
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  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognition/Decision making"
    ],
    [
      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Decision making"
    ],
    [
      "plos",
      "/Biology and life sciences/Psychology/Cognitive psychology/Decision making"
    ],
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      "plos",
      "/Biology and life sciences/Psychology/Psychometrics/Intelligence tests"
    ],
    [
      "plos",
      "/Computer and information sciences/Artificial intelligence"
    ],
    [
      "plos",
      "/Medicine and health sciences/Clinical medicine/Signs and symptoms/Fevers"
    ],
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      "plos",
      "/Medicine and health sciences/Diagnostic medicine"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors"
    ],
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      "plos",
      "/Medicine and health sciences/Medical conditions/Parasitic diseases/Malaria"
    ],
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      "plos",
      "/Medicine and health sciences/Medical conditions/Tropical diseases/Malaria"
    ],
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      "/Research and analysis methods/Database and informatics methods/Database searching"
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      "/Social sciences/Psychology/Cognitive psychology/Decision making"
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  "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001742&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/anhmr6r5zaspz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:37Z",
      "native_id": "10.1371/journal.pdig.0001742",
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  "subjects": [
    {
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      "origin": "plos:neuroscience",
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      "field": "medicine",
      "origin": "plos:epidemiology",
      "subfield": "epidemiology-public-health"
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  "title": "The use of artificial intelligence in assessing fever in the returning traveller: A scoping review",
  "title_text": "The use of artificial intelligence in assessing fever in the returning traveller: A scoping review",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:37Z",
  "url": "https://research.draconitic.com/paper/anhmr6r5zaspz",
  "venue": "PLOS Digital Health",
  "versions": []
}