Evidence map›Paper›PMID 39165388›Full record

ArticleDigital health

Enhancing health care through medical cognitive virtual agents.

Sushruta Mishra, Pamela Chaudhury, Hrudaya Kumar Tripathy, Kshira Sagar Sahoo, N Z Jhanjhi, Asma Abbas Hassan Elnour, Abdelzahir Abdelmaboud

Abstract read
In one paragraph

Article in Digital health. 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
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. 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

7 authors.

Sushruta MishraSchool of Computer Engineering, Kalinga Institute of Industrial Technology, deemed to be University, Bhubaneswar, India.
Pamela ChaudhuryDepartment of Computer Science and Engineering, Silicon Institute of Technology, Bhubaneswar, India.
Hrudaya Kumar TripathySchool of Computer Engineering, Kalinga Institute of Industrial Technology, deemed to be University, Bhubaneswar, India.
Kshira Sagar SahooDepartment of Computer Science and Engineering, SRM University, Amaravati, India.ORCID https://orcid.org/0000-0002-6435-5738
N Z JhanjhiSchool of Computer Science, SCS Taylor's University, Subang Jaya, Malaysia.ORCID https://orcid.org/0000-0001-8116-4733
Asma Abbas Hassan ElnourComputer Department, Applied College_ Girls Section, King Khalid University, Muhayel Aseer, Saudi Arabia.
Abdelzahir AbdelmaboudHumanities Research Center, Sultan Qaboos University, Muscat, Oman.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The modern era of cognitive intelligence in clinical space has led to the rise of 'Medical Cognitive Virtual Agents' (MCVAs) which are labeled as intelligent virtual assistants interacting with users in a context-sensitive and ambient manner. They aim to augment users' cognitive capabilities thereby helping both patients and medical experts in providing personalized healthcare like remote health tracking, emergency healthcare and robotic diagnosis of critical illness, among others. The objective of this study is to explore the technical aspects of MCVA and their relevance in modern healthcare. Methods: In this study, a comprehensive and interpretable analysis of MCVAs are presented and their impacts are discussed. A novel system framework prototype based on artificial intelligence for MCVA is presented. Architectural workflow of potential applications of functionalities of MCVAs are detailed. A novel MCVA relevance survey analysis was undertaken during March-April 2023 at Bhubaneswar, Odisha, India to understand the current position of MCVA in society. Results: Outcome of the survey delivered constructive results. Majority of people associated with healthcare showed their inclination towards MCVA. The curiosity for MCVA in Urban zone was more than in rural areas. Also, elderly citizens preferred using MCVA more as compared to youths. Medical decision support emerged as the most preferred application of MCVA. Conclusion: The article established and validated the relevance of MCVA in modern healthcare. The study showed that MCVA is likely to grow in future and can prove to be an effective assistance to medical experts in coming days.

Indexed as

chatbotsCognitive intelligencemedical cognitive virtual agentspatient educationpatient monitoringpersonalized health care

Identifiers

PMID39165388
PMCPMC11334247

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.