Evidence map›Paper›PMID 33748312›Full record

ArticleIEEE internet of things journal2020

A Survey of Healthcare Internet-of-Things (HIoT): A Clinical Perspective.

Hadi Habibzadeh, Karthik Dinesh, Omid Rajabi Shishvan, Andrew Boggio-Dandry, Gaurav Sharma, Tolga Soyata

Abstract read
In one paragraph

Article in IEEE internet of things journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 pooled it
–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

49 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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.

Hadi HabibzadehDepartment of Electrical and Computer Engineering, SUNY Albany, Albany NY, 12203.
Karthik DineshDepartment of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627.
Omid Rajabi ShishvanDepartment of Electrical and Computer Engineering, SUNY Albany, Albany NY, 12203.
Andrew Boggio-DandryDepartment of Electrical and Computer Engineering, SUNY Albany, Albany NY, 12203.
Gaurav SharmaDepartment of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627.
Tolga SoyataDepartment of Electrical and Computer Engineering, SUNY Albany, Albany NY, 12203.

Funding

The Clinical Core will support in-person and virtual research visits for three of the four Research Projects at the University of Rochester Udall CenterP50NS108676 · NINDS · UNIVERSITY OF ROCHESTER · PI DORSEY, EARL RAY · 2018 to 2022
$9.2M
NINDS NIH HHS P50 NS108676
6 · The paper itself

Abstract

In combination with current sociological trends, the maturing development of IoT devices is projected to revolutionize healthcare. A network of body-worn sensors, each with a unique ID, can collect health data that is orders-of-magnitude richer than what is available today from sporadic observations in clinical/hospital environments. When databased, analyzed, and compared against information from other individuals using data analytics, HIoT data enables the personalization and modernization of care with radical improvements in outcomes and reductions in cost. In this paper, we survey existing and emerging technologies that can enable this vision for the future of healthcare, particularly in the clinical practice of healthcare. Three main technology areas underlie the development of this field: (a) sensing, where there is an increased drive for miniaturization and power efficiency; (b) communications, where the enabling factors are ubiquitous connectivity, standardized protocols, and the wide availability of cloud infrastructure, and (c) data analytics and inference, where the availability of large amounts of data and computational resources is revolutionizing algorithms for individualizing inference and actions in health management. Throughout the paper, we use a case study to concretely illustrate the impact of these trends. We conclude our paper with a discussion of the emerging directions, open issues, and challenges.

Indexed as

clinical IoTdigital healthhealthcare analyticshealth managementhealth monitoringmedical decision support

Identifiers

PMID33748312
PMCPMC7970885

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.