ReviewDer Urologe. Ausg. A2020
[Surgery 4.0-are we ready?]
Review in Der Urologe. Ausg. A, 2020. 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
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.
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.
Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Requirement analysis for an AI-based AR assistance system for surgical tools in the operating room: stakeholder requirements and technical perspectives.International journal of computer assisted radiology and surgery · 2024Observational
- Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models.Sensors (Basel, Switzerland) · 2024Article
- Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry.Healthcare (Basel, Switzerland) · 2023Article
- What's new in artificially intelligent joint surgery in China? The minutes of the 2021 IEEE ICRA and literature review.Arthroplasty (London, England) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing networking of data systems in medicine is not only leading to modern interdisciplinarity in the sense of cooperation between different medical departments, but also poses new challenges regarding the building and room infrastructure. The surgical operating room of the future expands or augments its reality, away from the pure building characteristics, towards an intelligent and communicative space platform. The building infrastructure (operating theatre) serves as sensor and actuator. Thus, it is possible to inform about missing diagnostics as well as to register them directly in the contextualization of the planned surgical intervention or to integrate them into the processes. Integrated operating theatres represent a comprehensive computer platform based on a corresponding system architecture with software-based protocols. An underlying modular system consisting of various modules for image acquisition and analysis, interaction and visualization supports the integration and merging of heterogeneous data that are generated in a hospital operation. Integral building data (e.g., air conditioning, lighting control, device registration) are merged with patient-related data (age, type of illness, concomitant diseases, existing diagnostic CT and MRI images). New systems coming onto the market, as well as already existing systems will have to be measured by the extent to which they will be able to guarantee this integration of information-similar to the development from mobile phone to smartphone. Cost reduction should not be the only legitimizing argument for the market launch, but the vision of a new quality of surgical perception and action.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.