Evidence map›Paper›PMID 41727350›Full record

SynthesisFrontiers in artificial intelligence2025

Impact of Natural Language Processing models on diagnosis and decision-making in healthcare, business, education, and sports: a review.

Aryan Choudhary, Sireesha Pamidimokkala, Krithiga R, Bhavadharini R M

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in artificial intelligence, 2025. 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.

Aryan Choudhary *School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.
Sireesha Pamidimokkala *School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.
Krithiga RSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.
Bhavadharini R MSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural Language Processing (NLP) has an influence on almost every field nowadays, such as business, healthcare, and sports, by making advanced interactions with human language and providing analytics. In the field of business, NLP has been a revolution, bettering customer service with the help of advanced chatbots, sentiment analysis, and automation in generating content, which enhances efficiency, personalization, and most importantly, decision-making. In healthcare, NLP is of crucial importance in decoding unstructured data like of medical records, supporting diagnostic accuracy, and making patient communication smoother, leading to better outcomes and improving efficiency. When it comes to sports, NLP provides critical insights through performance analytics, media content interpretation, and improved fan engagement, transforming data to utilize it for our advantage. The aim of this review is to systematically evaluate NLP's effectiveness across these sectors, address possible and existing challenges, and propose approaches for future research. Through the integration of case studies and performance assessments, we seek to clearly explain how NLP promotes innovation, resolves complex issues, and has made contributions to advancing new heights in these domains.

Indexed as

BERTBusiness Process Modeling (BPM)Convolutional Neural Networks (CNN)Customer Relationship Management (CRM)Electronic Health Records (EHR)Named Entity Recognition (NER)Natural Language Processing (NLP)

Identifiers

PMID41727350
PMCPMC12918052

What OpenQuestion holds

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LicenceCC BY
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.