An observation support system with an adaptive ontology-driven user interface for the modeling of complex behaviors during surgical interventions

Neumuth, Thomas; Kaschek, B.; Neumuth, Dayana; Ceschia, M.; Meixensberger, Jürgen; Strauß, Gero; Burgert, Oliver

doi:10.3758/brm.42.4.1049

Cited by 11 publications

(10 citation statements)

References 30 publications

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“…With this, it is possible to describe SPMs in laparoscopy in a vocabulary familiar to surgeons. This is similar to the approach presented by Neumuth et al [19]; however, OntoSPM is much more focused on the representation of the actual workflow and less on the linguistic and mathematical levels seen in this approach. In OntoSPM, the classes specified in the Terminological Box (TBox) model classes and object properties relevant to the domain of surgical procedures, whereas the Assertional Box (ABox) contains assertions about real-world entities such as actual performed procedures or completed actions and their concrete participants.…”

Section: Formalization Of Laparoscopic Surgeriesmentioning

confidence: 76%

“…A related field is the area of surgical evaluation, where similar methods are used to assess the performance of the surgeon [22]. With the notable exception of [19,20] with its broad scope, most works that do represent knowledge formally, sharing of knowledge and data, are seldom a consideration. In contrast, other research fields put emphasize on data sharing [23].…”

Section: Introductionmentioning

confidence: 99%

“…Top-down approaches, in contrast, aim to formalize medical knowledge generically [16]. Formal methods such as Description Logics (DL) [17] or UML [18] and ontological descriptions [19] are used for this purpose. Specifically, Neumuth et al have developed an approach for surgical process modeling with a heavy emphasis on linguistic understandability, statistical analysis and data mining.…”

Section: Introductionmentioning

confidence: 99%

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LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

et al. 2015

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We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data representation in the field on context awareness and thus toward unified benchmark data sets.

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Section: Formalization Of Laparoscopic Surgeriesmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

et al. 2015

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“…The idea is to formalize medical knowledge generically [17]. Description logics (DL) [18], UML [19] and ontological descriptions [20] are used for this purpose. Neumuth et al have proposed an approach for surgical process modeling with an emphasis on linguistic understandability.…”

Section: Introductionmentioning

confidence: 99%

Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy

et al. 2016

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“…In [25,26], a quick and flexible strategy for the acquisition of data produced by different entities in the OR by means of observation has been described. This strategy is based on the definition mentioned above, namely, that a surgical process is a succession of surgical work-steps [27][28][29].…”

Section: Data Acquisition By Observationmentioning

confidence: 99%

Surgical process modeling

Neumuth

2017

Innovative Surgical Sciences

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Due to the rapidly evolving medical, technological, and technical possibilities, surgical procedures are becoming more and more complex. On the one hand, this offers an increasing number of advantages for patients, such as enhanced patient safety, minimal invasive interventions, and less medical malpractices. On the other hand, it also heightens pressure on surgeons and other clinical staff and has brought about a new policy in hospitals, which must rely on a great number of economic, social, psychological, qualitative, practical, and technological resources. As a result, medical disciplines, such as surgery, are slowly merging with technical disciplines. However, this synergy is not yet fully matured. The current information and communication technology in hospitals cannot manage the clinical and operational sequence adequately. The consequences are breaches in the surgical workflow, extensions in procedure times, and media disruptions. Furthermore, the data accrued in operating rooms (ORs) by surgeons and systems are not sufficiently implemented. A flood of information, "big data", is available from information systems. That might be deployed in the context of Medicine 4.0 to facilitate the surgical treatment. However, it is unused due to infrastructure breaches or communication errors. Surgical process models (SPMs) alleviate these problems. They can be defined as simplified, formal, or semiformal representations of a network of surgery-related activities, reflecting a predefined subset of interest. They can employ different means of generation, languages, and data acquisition strategies. They can represent surgical interventions with high resolution, offering qualifiable and quantifiable information on the course of the intervention on the level of single, minute, surgical work-steps. The basic idea is to gather information concerning the surgical intervention and its activities, such as performance time, surgical instrument used, trajectories, movements, or intervention phases. These data can be gathered by means of workflow recordings.These recordings are abstracted to represent an individual surgical process as a model and are an essential requirement to enable Medicine 4.0 in the OR. Further abstraction can be generated by merging individual process models to form generic SPMs to increase the validity for a larger number of patients. Furthermore, these models can be applied in a wide variety of use-cases. In this regard, the term "modeling" can be used to support either one or more of the following tasks: "to describe", "to understand", "to explain", to optimize", "to learn", "to teach", or "to automate". Possible use-cases are requirements analyses, evaluating surgical assist systems, generating surgeon-specific training-recommendation, creating workflow management systems for ORs, and comparing different surgical strategies. The presented chapter will give an introduction into this challenging topic, presenting different methods to generate SPMs from the workflow in the OR, as well as various...

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An observation support system with an adaptive ontology-driven user interface for the modeling of complex behaviors during surgical interventions

Cited by 11 publications

References 30 publications

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy

Surgical process modeling

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