Evidence map›Paper›PMID 21667099›Full record

ArticleJournal of medical systems2012

Computerized disease profiling using GPS-linked multi-function sensor cartridges.

Daniel Lorence, Joseph Wu

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 83% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Daniel LorenceCenter for Technology Assessment, State College, PA, USA. danlor467@yahoo.com
Joseph Wu
Center for Assessment · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease identification in public health monitoring routinely employs analyte detection systems capable of discriminating mixtures of analytes, toxins, cells and/or bacteria in medical and/or environmental solutions. The development of smart sensors capable of discriminating such compounds has become increasingly important for clinical, environmental, and health applications. While some sensors have been fashioned for single analyte detection, methods and systems that facilitate rapid screening of multiple clinical components are needed, serving as triggers for potential epidemics or more specific confirmatory testing. In public health applications, there is like need for immediate collection of geocoded data tagged by disease identification characteristics, with corresponding alerting capabilities. In this technology review we propose one promising model for using a combination of emerging systems-based technologies in multi sensor cartridges, integrated with GPS-enabled, alert-capable mobile phone devices.

Indexed as

Geographic Information SystemsDiagnosis, Computer-AssistedModels, TheoreticalMonitoring, PhysiologicPopulation SurveillancePublic HealthUnited States

Identifiers

PMID21667099
OpenAlexW2163666806

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.