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Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review
Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228894/ https://www.ncbi.nlm.nih.gov/pubmed/35746144 http://dx.doi.org/10.3390/s22124362 |
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author | Gulzar Ahmad, Saima Iqbal, Tassawar Javaid, Anam Ullah Munir, Ehsan Kirn, Nasira Ullah Jan, Sana Ramzan, Naeem |
author_facet | Gulzar Ahmad, Saima Iqbal, Tassawar Javaid, Anam Ullah Munir, Ehsan Kirn, Nasira Ullah Jan, Sana Ramzan, Naeem |
author_sort | Gulzar Ahmad, Saima |
collection | PubMed |
description | Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers. |
format | Online Article Text |
id | pubmed-9228894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92288942022-06-25 Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review Gulzar Ahmad, Saima Iqbal, Tassawar Javaid, Anam Ullah Munir, Ehsan Kirn, Nasira Ullah Jan, Sana Ramzan, Naeem Sensors (Basel) Review Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers. MDPI 2022-06-09 /pmc/articles/PMC9228894/ /pubmed/35746144 http://dx.doi.org/10.3390/s22124362 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Gulzar Ahmad, Saima Iqbal, Tassawar Javaid, Anam Ullah Munir, Ehsan Kirn, Nasira Ullah Jan, Sana Ramzan, Naeem Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title | Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title_full | Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title_fullStr | Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title_full_unstemmed | Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title_short | Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review |
title_sort | sensing and artificial intelligent maternal-infant health care systems: a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228894/ https://www.ncbi.nlm.nih.gov/pubmed/35746144 http://dx.doi.org/10.3390/s22124362 |
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