Evidence map›Paper›PMID 31802856›Full record

ArticlePatient preference and adherence2019

Attitudes Of Chinese Cancer Patients Toward The Clinical Use Of Artificial Intelligence.

Keyi Yang, Zhi Zeng, Hu Peng, Yu Jiang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Patient preference and adherence, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
1.0field-weighted citation impact, top 16% of its field
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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. The use of generative AI tools among individuals with cancer and their caregivers: a cross-sectional study of awareness, attitudes, and experiences.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  12. Artificial Intelligence in Medical Care - Patients' Perceptions on Caregiving Relationships and Ethics: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  13. Understanding Public Judgements on Artificial Intelligence in Healthcare: Dialogue Group Findings From Australia.Health expectations : an international journal of public participation in health care and health policy · 2025
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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

4 authors at 1 institution in 1 country.

Keyi YangDepartment of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.ORCID 0000-0001-5659-888X
Zhi ZengDepartment of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
Hu PengDepartment of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
Yu JiangDepartment of Head and Neck Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeArtificial intelligence (AI) plays a substantial role in many domains, including medical fields. However, we still lack evidence to support whether or not cancer patients will accept the clinical use of AI. This research aims to assess the attitudes of Chinese cancer patients toward the clinical use of artificial intelligence in medicine (AIM), and to analyze the possible influencing factors. PATIENTS AND

methodsA questionnaire was delivered to 527 participants. Targeted people were Chinese cancer patients who were informed of their cancer diagnosis.

resultsThe effective response rate was 76.3% (402/527). Most cancer patients trusted AIMs in both stages of diagnosis and treatment, and participants who had heard of AIMs were more likely to trust them in the diagnosis phase. When an AIM's diagnosis diverged from a human doctor' s, ethnic minorities, and those who had received traditional Chinese medicine (TCM), had never received chemotherapy, were more likely to choose "AIM", and when an AIM's therapeutic advice diverged from a human doctor's, male participants, and those who had received TCM or surgery, were more likely to choose "AIM".

conclusionMost Chinese cancer patients believed in the AIM to some extent. Nevertheless, most still thought that oncology physicians were more trustworthy when their opinions diverged. Participants' gender, race, treatment received, and AIM related knowledge might influence their attitudes toward the AIM. Most participants thought AIM would assist oncology physicians in the future, while little really believed that oncology physicians would completely be replaced.

Indexed as

artificial intelligenceattitudecancercancer patientclinical useoncology

Identifiers

PMID31802856
PMCPMC6830378
OpenAlexW2982471526

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.