ArticleInternational journal of computer assisted radiology and surgery2025
German surgeons' perspective on the application of artificial intelligence in clinical decision-making.
Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Artificial intelligence and chatbots in general surgery: a survey among surgeons in Germany, Austria and Switzerland.Surgical endoscopy · 2026Article
- Towards clinically interpretable machine learning in emergency surgery: feature importance and insights across clinical time points in abdominal pain cases.Langenbeck's archives of surgery · 2026Article
- Challenges in clinical translation of artificial intelligence and real-time imaging navigation in radical gastrectomy.World journal of gastroenterology · 2025Review
- Artificial Intelligence in Primary Care Decision-Making: Survey of Healthcare Professionals in Saudi Arabia.Cureus · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeArtificial intelligence (AI) is transforming clinical decision-making (CDM). This application of AI should be a conscious choice to avoid technological determinism. The surgeons' perspective is needed to guide further implementation.
methodsWe conducted an online survey among German surgeons, focusing on digitalization and AI in CDM, specifically for acute abdominal pain (AAP). The survey included Likert items and scales.
resultsWe analyzed 263 responses. Seventy-one percentage of participants were male, with a median age of 49 years (IQR 41-57). Seventy-three percentage of participants carried out a senior role, with a median of 22 years of work experience (IQR 13-28). AI in CDM was seen as helpful for workload management (48%) but not for preventing unnecessary treatments (32%). Safety (95%), evidence (94%), and usability (96%) were prioritized over costs (43%) for the implementation. Concerns included the loss of practical CDM skills (81%) and ethical issues like transparency (52%), patient trust (45%), and physician integrity (44%). Traditional CDM for AAP was seen as experience-based (93%) and not standardized (31%), whereas AI was perceived to assist with urgency triage (60%) and resource management (59%). On median, generation Y showed more confidence in AI for CDM (P = 0.001), while participants working in primary care hospitals were less confident (P = 0.021).
conclusionParticipants saw the potential of AI for organizational tasks but are hesitant about its use in CDM. Concerns about trust and performance need to be addressed through education and critical evaluation. In the future, AI might provide sufficient decision support but will not replace the human component.
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Registered trials
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.