Evidence map›Paper›PMID 39128072›Full record

ArticleThe Eurasian journal of medicine2023

Artificial Intelligence in Breast Imaging: Opportunities, Challenges, and Legal-Ethical Considerations.

Irmak Durur Subasi, Ş Barış Özçelik

Abstract read
In one paragraph

Article in The Eurasian journal of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

2 authors.

Irmak Durur SubasiIstanbul Medipol University International Faculty of Medicine, Istanbul, Turkey.
Ş Barış ÖzçelikBilkent University Faculty of Law, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review explores the transformative impact of artificial intelligence (AI) in breast imaging, driven by a global rise in breast cancer cases. Propelled by deep learning techniques, AI shows promise in refining diagnostic processes, yet adoption rates vary. Its ability to manage extensive datasets and process multidimensional information holds potential for advancing precision medicine in breast cancer research. However, integration faces challenges, from data-related obstacles to ensuring transparency and trust in decision-making. Legal considerations, including the formation of AI teams and intellectual property protection, influence health care's adoption of AI. Ethical dimensions underscore the need for responsible AI implementation, emphasizing autonomy, well-being, safety, transparency, and accessibility. Establishing a robust legal and ethical framework is crucial for conscientiously deploying AI, ensuring positive impacts on patient safety and treatment efcacy. As nations and organizations aspire to engage in global competition, not merely as consumers, the review highlights the critical importance of developing legal regulations. A comprehensive approach, from AI team formation to end-user processes, is essential for navigating the complex terrain of AI applications in breast imaging. Legal experts play a key role in ensuring compliance, managing risks, and fostering resilient integration. The ultimate goal is a harmonious synergy between technological advancements and ethical considerations, ushering in enhanced breast cancer diagnostics through responsible AI utilization.

Identifiers

PMID39128072
PMCPMC11075018

What OpenQuestion 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 OpenQuestion graph.