Advancements and gaps in natural language processing and machine learning applications in healthcare - a comprehensive review of electronic medical records and medical imaging

Aug 5, 2026

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The review examines progress and limitations in Natural Language Processing (NLP) and Machine Learning (ML), especially Deep Learning (DL), within healthcare. It synthesizes how these methods support Electronic Medical Records (EMRs) and extends coverage to medical imaging as a complementary area. Using literature published from 2015 to 2023 and applying defined inclusion criteria, 100 papers are analyzed from databases such as SCOPUS. Findings show NLP and image processing improve decision-making, extract insights from unstructured data, and enhance diagnostic accuracy while exposing gaps in scalability, ethics, collaboration, longitudinal analysis, and domain-specific customization.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages16

Reading Time40 min

AccessFree to download

Introduction

Background

Review Scope and Methods

Literature selection (2015–2023)

Inclusion criteria and assessment

Applications in Electronic Medical Records

Information extraction and decision support

Applications in Medical Imaging

Image processing and diagnosis support

Key Findings

Progress in accuracy and patient care

Identified Gaps and Future Directions

Scalability, ethics, collaboration, longitudinal data

TYPE Review PUBLISHED 02 December 2024 DOI 10.3389/fphy.2024.1445204 OPEN ACCESS EDITED BY Federico Giove, Centro Fermi-Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Italy REVIEWED BY Yunfei Long, University of Essex, United Kingdom Mayuri Mehta, Sarvajanik College of Engineering and Technology, India Dweepna Garg, Charotar University of Science and Technology, India Amit Ganatra, Parul University, India *CORRESPONDENCE Shilpa Gite, [shilpa.gite@sitpune.edu.in](shilpa.gite@sitpune.edu.in)[ ](shilpa.gite@sitpune.edu.in)Biswajeet Pradhan, [Biswajeet.Pradhan@uts.edu.au](Biswajeet.Pradhan@uts.edu.au)[ ](Biswajeet.Pradhan@uts.edu.au)Chang-Wook Lee, [cwlee@kangwon.ac.kr](cwlee@kangwon.ac.kr) RECEIVED 06 June 2024 ACCEPTED 06 November 2024 PUBLISHED 02 December 2024 CITATION Khalate P, Gite S, Pradhan B and Lee C-W (2024) Advancements and gaps in natural language processing and machine learning applications in healthcare: a comprehensive review of electronic medical records and medical imaging. Front. Phys. 12:1445204 . doi: 10.3389/fphy.2024.1445204 COPYRIGHT © 2024 Khalate, Gite, Pradhan and Lee. This isan open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Advancements and gaps in natural language processing and machine learning applications in healthcare: a comprehensive review of electronic medical records and medical imaging Priyanka Khalate 1, Shilpa Gite 1,2*, Biswajeet Pradhan 3* and Chang-Wook Lee 4* 1AI and ML Department, Symbiosis Institute of Technology (Pune Campus), Symbiosis International Deemed University, Pune, India, 2Symbiosis Centre for Applied Artificial Intelligence, Symbiosis Institute of Technology (Pune Campus), Symbiosis International Deemed University, Pune, India, 3Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW, Australia, 4 Department of Science Education, Kangwon National University, Chuncheon, Republic of Korea This article presents a thorough examination of the progress and limitations in the application of Natural Language Processing (NLP) and Machine Learning (ML), particularly Deep Learning (DL), in the healthcare industry. This paper examines the progress and limitations in the utilisation of Natural Language Processing (NLP) and Machine Learning (ML) in the healthcare field, specifically in relation to Electronic Medical Records (EMRs) . The review also examines the incorporation of Natural Language Processing (NLP) and Machine Learning (ML) in medical imaging as a supplementary field, emphasising the transformative impact of these technologies on the analysis of healthcare data and patient care. This review attempts to analyse both fields in order to offer insights into the current state of research and suggest potential chances for future advancements. The focus is on the use of these technologies in Electronic Medical Records (EMRs) and medical imaging. The review methodically detects, chooses, and assesses literature published between 2015 and 2023, utilizing keywords pertaining to natural language processing (NLP) and healthcare in databases such as SCOPUS. After applying precise inclusion criteria, 100 papers were thoroughly examined. The paper emphasizes notable progress in utilizing NLP and ML methodologies to improve healthcare decisionmaking, extract information from unorganized data, and evaluate medical pictures. The key findings highlight the successful combination of nat

FAQs

What areas does the review focus on in healthcare applications of NLP and ML?

It focuses on NLP and ML for Electronic Medical Records (EMRs) and on their use in medical imaging as a supplementary field.

How was the literature in the review selected and evaluated?

The review methodically detects, selects, and assesses literature published between 2015 and 2023 using relevant keywords in databases such as SCOPUS, and applies precise inclusion criteria before examining 100 papers.

What gaps does the review identify for future work?

It highlights needs for scalable practical implementations, stronger interdisciplinary collaboration, explicit ethical considerations, analysis of longitudinal patient data, and customization of approaches for specific medical situations.

Aug 5, 2026

Upload by Asher