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Record W1982890084 · doi:10.1109/bwcca.2011.59

A Survey on Home Telemedicine

2011· article· en· W1982890084 on OpenAlexaff
Kin Fun Li, Wei Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTelemedicineThe InternetMobile deviceWork (physics)Computer scienceHealth careInternet privacyTelecommunicationsPopulationHome healthMultimediaWorld Wide WebBusinessMedicineEngineeringEnvironmental health

Abstract

fetched live from OpenAlex

With the aging population, mobility is an important issue and thus restricts the elderlies to visit health clinics on a regular basis. Also, people living in remote areas often do not get the needed health care unless they are willing to travel. Advances in information and telecommunication technologies have made telemedicine possible. Using the latest sensor technologies, bio-information can be transferred wirelessly or via the Internet between home or handheld devices with the centralized database storage. People can use sensing apparatus at home and the collected health signals and information can be monitored on a real-time or archival basis remotely. Medical practitioners can therefore provide services to more people. This work surveys and compiles the relevant home telemedicine technologies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

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

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 head0.073
GPT teacher head0.252
Teacher spread0.179 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2011
Admission routes1
Has abstractyes

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