Evidence map›Paper›PMID 39998782›Full record

ReviewCurrent oncology reports2025

ChatGPT in Oncology Diagnosis and Treatment: Applications, Legal and Ethical Challenges.

Zihan Zhou, Peng Qin, Xi Cheng, Maoxuan Shao, Zhaozheng Ren, Yiting Zhao, Qiunuo Li, Lingxiang Liu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current oncology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
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  4. Review
  5. Article
  6. Article
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  9. Article
  10. Traditional Chinese Medicine Treatment of Thyroid Cancer: A Review.International journal of general medicine · 2025
    Review
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

8 authors.

Zihan ZhouThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Peng QinThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Xi ChengThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Maoxuan ShaoThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Zhaozheng RenThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Yiting ZhaoStomatological College of Nanjing Medical University, Nanjing, 211166, China.
Qiunuo LiThe First Clinical Medical College of Nanjing Medical University, Nanjing, 211166, China.
Lingxiang LiuDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China. llxlau@163.com.

Funding

The Chinese Ministry of Education 202310312139E
6 · The paper itself

Abstract

purpose of reviewThis study aims to systematically review the trajectory of artificial intelligence (AI) development in the medical field, with a particular emphasis on ChatGPT, a cutting-edge tool that is transforming oncology's diagnosis and treatment practices. RECENT

findingsRecent advancements have demonstrated that ChatGPT can be effectively utilized in various areas, including collecting medical histories, conducting radiological & pathological diagnoses, generating electronic medical record (EMR), providing nutritional support, participating in Multidisciplinary Team (MDT) and formulating personalized, multidisciplinary treatment plans. However, some significant challenges related to data privacy and legal issues that need to be addressed for the safe and effective integration of ChatGPT into clinical practice. ChatGPT, an emerging AI technology, opens up new avenues and viewpoints for oncology diagnosis and treatment. If current technological and legal challenges can be overcome, ChatGPT is expected to play a more significant role in oncology diagnosis and treatment in the future, providing better treatment options and improving the quality of medical services.

Indexed as

Artificial IntelligenceMedical OncologyNeoplasmsElectronic Health RecordsGenerative Artificial IntelligenceHumansArtificial IntelligenceChatGPTData PrivacyLarge Language ModelsMedical ImagingOncology Treatment

Identifiers

What OpenQuestion holds

Textmetadata
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.