Optimized port placement for <i>in vivo</i> biosensors

King, Brady W.; Reisner, Luke A.; Ellis, R. Darin; Klein, Michael D.; Auner, Gregory W.; Pandya, Abhilash

doi:10.1002/rcs.257

Cited by 3 publications

(5 citation statements)

References 23 publications

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“…This was similarly discussed in 2009 by King et al, where medical imaging data was used to reconstruct 3D regions. This was done to optimise port placement for in vivo biosensors [7]. Porro et al, in 2005, used recorded clinical data in the form of DICOM images, either from recent patients or from archives, to create 3D reconstructions [8].…”

Section: Resultsmentioning

confidence: 99%

On the usage of health records for the design of virtual patients: a systematic review

Bloice

Simonic

Holzinger

2013

BMC Med Inform Decis Mak

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BackgroundThe process of creating and designing Virtual Patients for teaching students of medicine is an expensive and time-consuming task. In order to explore potential methods of mitigating these costs, our group began exploring the possibility of creating Virtual Patients based on electronic health records. This review assesses the usage of electronic health records in the creation of interactive Virtual Patients for teaching clinical decision-making.MethodsThe PubMed database was accessed programmatically to find papers relating to Virtual Patients. The returned citations were classified and the relevant full text articles were reviewed to find Virtual Patient systems that used electronic health records to create learning modalities.ResultsA total of n = 362 citations were found on PubMed and subsequently classified, of which n = 28 full-text articles were reviewed. Few articles used unformatted electronic health records other than patient CT or MRI scans. The use of patient data, extracted from electronic health records or otherwise, is widespread. The use of unformatted electronic health records in their raw form is less frequent. Patient data use is broad and spans several areas, such as teaching, training, 3D visualisation, and assessment.ConclusionsVirtual Patients that are based on real patient data are widespread, yet the use of unformatted electronic health records, abundant in hospital information systems, is reported less often. The majority of teaching systems use reformatted patient data gathered from electronic health records, and do not use these electronic health records directly. Furthermore, many systems were found that used patient data in the form of CT or MRI scans. Much potential research exists regarding the use of unformatted electronic health records for the creation of Virtual Patients.

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Section: Resultsmentioning

confidence: 99%

On the usage of health records for the design of virtual patients: a systematic review

Bloice

Simonic

Holzinger

2013

BMC Med Inform Decis Mak

View full text Add to dashboard Cite

show abstract

“…This software application is a medical imaging package capable of displaying 3D representations of data, such as CT or MRI scans of patients. 3D Slicer was modified to incorporate the port placement algorithms described in (15). In addition, functions were added to collect data, such as the chosen port location during the testing.…”

Section: Apparatusmentioning

confidence: 99%

“…In addition, the system has methods for evaluating (based on geometric and sensor constraints) the placement of a port chosen by a user. The implementation details of the system are presented in another paper (15).…”

Section: Introductionmentioning

confidence: 99%

“…Using the automated port placement system's evaluation methods, we grade user-specified placement (15). Such an evaluation has never been done before because biosensor use has not been prevalent in surgery and no grading system was available for this type of port placement task.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, we have developed an automated port placement system that focuses on biosensors (15). The system utilizes 3D representations of a patient's anatomy derived from medical imaging (such as CT or MRI) and allows target areas to be selected by the surgeon.…”

Section: Introductionmentioning

confidence: 99%

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