Evidence map›Paper›PMID 42221159›Full record

ArticleFrontiers in digital health2026

Development of reconfigurable smart medical wards using integrated components and complex features.

Ramesh Kumar Veerapaneni, Radhakrishnan Delhibabu, Dmitriy Levonevskiy, Nataly Zhukova

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ramesh Kumar VeerapaneniSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Radhakrishnan DelhibabuSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Dmitriy LevonevskiyLaboratory of Big Data Technologies in Socio-Cyberphysical Systems, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), Saint Petersburg, Russia.
Nataly ZhukovaLaboratory of Big Data Technologies in Socio-Cyberphysical Systems, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), Saint Petersburg, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient treatment in hospitals requires their regular monitoring to assess their health conditions. At the same time, routine measurements are often delayed, missed, or not analyzed, and this situation worsens at night and on weekends due to reduced staffing, which in turn affects the quality of treatment. Innovations in the field of infocommunication technologies allow the healthcare industry to enhance the provided medical services. One of the promising areas is the creation of smart wards so that the patient information will be easily accessible and properly analyzed, with real-time alerts sent to healthcare professionals. Assessing health and diagnosing diseases require data collection and processing techniques that can be implemented by the smart ward modules. The variety of data, situations, diseases, and techniques creates the need to simplify and speed up the development of such modules and to increase the reusability of such development. In this work, we propose a method that allows the creation of applications as integrated components for smart wards for assessing patient health using complex feature techniques. The proposed method provides the necessary software flexibility and reusability for smart wards, enabling dynamic construction of processing pipelines. Thus, it becomes possible to reduce labor costs not only in the application usage but also in the development of such components.

Indexed as

applications in medicineautomation of medicinecomplex featuresdisease diagnosticssmart ward

Identifiers

PMID42221159
PMCPMC13219344

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Registered trials

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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.