Evidence map›Paper›PMID 39202068›Full record

ReviewJournal of personalized medicine2024

Chatbots in Cancer Applications, Advantages and Disadvantages: All that Glitters Is Not Gold.

Georgios Goumas, Theodoros I Dardavesis, Konstantinos Syrigos, Nikolaos Syrigos, Effie Simou

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Evidence-Based Analysis of AI Chatbots in Oncology Patient Education: Implications for Trust, Perceived Realness, and Misinformation Management.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025
    Review
  9. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Georgios GoumasDepartment of Public Health Policy, School of Public Health, University of West Attica, 115 21 Athens, Greece.ORCID 0009-0008-5940-2043
Theodoros I DardavesisLaboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece.
Konstantinos SyrigosOncology Unit, 3rd Department of Medicine, "Sotiria" Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, 115 27 Athens, Greece.
Nikolaos SyrigosOncology Unit, 3rd Department of Medicine, "Sotiria" Hospital for Diseases of the Chest, National and Kapodistrian University of Athens, 115 27 Athens, Greece.ORCID 0000-0001-8082-594X
Effie SimouDepartment of Public Health Policy, School of Public Health, University of West Attica, 115 21 Athens, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of digitalization and artificial intelligence has had a profound impact on society, especially in the field of medicine. Digital health is now a reality, with an increasing number of people using chatbots for prognostic or diagnostic purposes, therapeutic planning, and monitoring, as well as for nutritional and mental health support. Initially designed for various purposes, chatbots have demonstrated significant advantages in the medical field, as indicated by multiple sources. However, there are conflicting views in the current literature, with some sources highlighting their drawbacks and limitations, particularly in their use in oncology. This state-of-the-art review article seeks to present both the benefits and the drawbacks of chatbots in the context of medicine and cancer, while also addressing the challenges in their implementation, offering expert insights on the subject.

Indexed as

advantagesartificialcancerchallengeschatbotsdisadvantageshealthintelligencemedicine

Identifiers

PMID39202068
PMCPMC11355580

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.