Evidence map›Paper›PMID 32360265›Full record

ArticleJournal of biomedical informatics2020

INSMA: An integrated system for multimodal data acquisition and analysis in the intensive care unit.

Yingcheng Sun, Fei Guo, Farhad Kaffashi, Frank J Jacono, Michael DeGeorgia, Kenneth A Loparo

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Quantifying the Suitability of Biosignals Acquired During Surgery for Multimodal Analysis.IEEE open journal of engineering in medicine and biology · 2024
    Article
  4. Article
  5. Observational
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

6 authors.

Yingcheng SunCDS Department, Case Western Reserve University, Cleveland, OH, United States. Electronic address: yxs489@case.edu.
Fei GuoECSE Department, Case Western Reserve University, Cleveland, OH, United States.
Farhad KaffashiECSE Department, Case Western Reserve University, Cleveland, OH, United States.
Frank J JaconoDepartment of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Michael DeGeorgiaDepartment of Neurology, Case Western Reserve University, Cleveland, OH, United States.
Kenneth A LoparoECSE Department, Case Western Reserve University, Cleveland, OH, United States.

Funding

Targeted Delivery of Multi-Parametic Telemetry Clinical Messages to Mitigate AlarR18HS022860 · AHRQ · RHODE ISLAND HOSPITAL · PI KOBAYASHI, LEO · 2014 to 2016
$746k
AHRQ HHS R18 HS022860
6 · The paper itself

Abstract

Modern intensive care units (ICU) are equipped with a variety of different medical devices to monitor the physiological status of patients. These devices can generate large amounts of multimodal data daily that include physiological waveform signals (arterial blood pressure, electrocardiogram, respiration), patient alarm messages, numeric vitals data, etc. In order to provide opportunities for increasingly improved patient care, it is necessary to develop an effective data acquisition and analysis system that can assist clinicians and provide decision support at the patient bedside. Previous research has discussed various data collection methods, but a comprehensive solution for bedside data acquisition to analysis has not been achieved. In this paper, we proposed a multimodal data acquisition and analysis system called INSMA, with the ability to acquire, store, process, and visualize multiple types of data from the Philips IntelliVue patient monitor. We also discuss how the acquired data can be used for patient state tracking. INSMA is being tested in the ICU at University Hospitals Cleveland Medical Center.

Indexed as

Intensive Care UnitsEquipment FailureHumansMonitoring, PhysiologicIntensive care unitMedical data miningMultimodal dataPhilips IntelliVue patient monitor

Identifiers

PMID32360265
PMCPMC7187847

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.