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Record W1852994921 · doi:10.4103/0974-2700.86654

Telementorable "just-in-time" lung ultrasound on an iPhone

2011· article· en· W1852994921 on OpenAlexaffabout
AndrewW Kirkpatrick, Innes Crawford, PaulB McBeth, Mark Mitchelson, Corina Tiruta, James Ferguson

Bibliographic record

VenueJournal of Emergencies Trauma and Shock · 2011
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsComputer scienceLaptopMedical physicsMedicineMultimedia

Abstract

fetched live from OpenAlex

Sir, Pleural and lung ultrasound (PLUS) is increasingly used in the bedside management of pulmonary pathology such as with the EFAST and BLUE protocols.[12] As ultrasound is operator-dependent, however, there are challenges to ensure that clinicians have adequate training. With a current explosion in the availability of ultrasound machines, we believe there is a need to optimize ultrasound availability to patients, yet ensure quality and avoidance of misinformation from erroneous exams. The National Aeronautics and Space Administration has addressed this challenge by examining the concept of remote telementored telesonography (RTMTS), wherein just-in-time users onboard the International Space Station are guided to capture meaningful images by remote terrestrial experts using elaborate informatics.[3] The World Health Organization also recognizes that communication technologies have the potential to address challenges in both developed and developing countries in providing accessible, cost-effective, and high-quality healthcare services, especially for rural and underserved communities in developing countries.[4] Thus, we endeavored to provide RTMTS using markedly simpler informatics.[5] We investigated the provision of RTMS by allowing remote experts in Aberdeen to view real-time PLUS images displayed on a smartphone (iPhone-4, Apple, Cupertino, CA). A portable ultrasound (Sonosite 180, Sonosite, Bothell, WA) in Calgary was interfaced to a laptop computer (Aspire 5741, Acer, Kuala Lumpur, Malaysia) via an analogue-to-digital converter (VC-211V, ActionStar LinXcel, Taiwan) [Figure on-line supplement]. Xsplit Broadcaster (SplitMediaLabs ltd, Hong Kong) allowed video-streaming of both an inexpensive head-mounted webcam (LifeCam VX-2000, Microsoft, Washington) and ultrasound over Skype (Skype, Luxembourg), easily viewed on any smartphone. The remote experts were thereafter able to easily view both the Calgary examiners hands and probe and resultant ultrasound images and to audibly bidirectionally communicate during the conducting of PLUS, with the iphone images deemed of diagnostic quality demonstrating clear evidence of real-time lung sliding [Figure 1]. While best appreciated real-time, the color-power Doppler function also documented this movement as the “Power-slide,”[6] confirming and documenting respiration and pneumothorax absence.Figure 1: iPhone image as viewed in Aberdeen demonstrating the “Power slide” confirming pleural sliding with imbedded image of remote examiner holding US probe in CalgaryWhile ultrasound images have been previously viewed over smartphones, we believe this is the first utilization of this ever more-prevalent technology to allow cost-minimal telementoring in lung telesonography. Therefore, despite the myriad of challenges for global health improvements, we believe that as the globe is shrunk by informatics, remote experts in developed nations could increasingly assist with education and clinical care delivery using affordable technologies that are likely to be already in our coat pockets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.337
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2011
Admission routes2
Has abstractyes

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