Evidence map›Paper›PMID 33771068›Full record

ArticleThe Journal of international medical research2021

Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies.

Lushun Jiang, Zhe Wu, Xiaolan Xu, Yaqiong Zhan, Xuehang Jin, Li Wang, Yunqing Qiu

Open access · goldAbstract read
In one paragraph

Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 4 pooled it
7.2field-weighted citation impact, top 3% 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

73 citing papers in PubMed, 4 syntheses or guidelines pooled it, 183 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

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

7 authors at 2 institutions in 1 country.

Lushun JiangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.ORCID https://orcid.org/0000-0002-4026-7418
Zhe WuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
Xiaolan XuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
Yaqiong ZhanState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
Xuehang JinState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
Li WangDepartment of Rehabilitation Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
Yunqing QiuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China.
State Key Laboratory of Diagnosis and Treatment of Infectious DiseasesZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in the field of artificial intelligence have demonstrated success in a variety of clinical tasks secondary to the development and application of big data, supercomputing, sensor networks, brain science, and other technologies. However, no projects can yet be used on a large scale in real clinical practice because of the lack of standardized processes, lack of ethical and legal supervision, and other issues. We analyzed the existing problems in the field of artificial intelligence and herein propose possible solutions. We call for the establishment of a process framework to ensure the safety and orderly development of artificial intelligence in the medical industry. This will facilitate the design and implementation of artificial intelligence products, promote better management via regulatory authorities, and ensure that reliable and safe artificial intelligence products are selected for application.

Indexed as

Artificial IntelligenceHumansArtificial intelligenceclinical decision supportclinical practiceclosed-loop frameworkmachine learningmedical industryregulation

Identifiers

PMID33771068
PMCPMC8165857
OpenAlexW3138769367

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.