Special Issue "Feature Papers in Medical and Clinical Informatics"

A special issue of Informatics (ISSN 2227-9709). This special issue belongs to the section "Medical and Clinical Informatics".

Deadline for manuscript submissions: 31 August 2022 | Viewed by 4341

Special Issue Editor

Dr. Jiang Bian
E-Mail Website
Guest Editor
Biomedical Informatics, Department of Health Outcomes & Policy, College of Medicine, University of Florida, Gainesville, FL 32610, USA
Interests: social media; network science; machine learning; data privacy; security; health outcomes; health information; clinical informatics; consumer health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomedical and health informatics is “the interdisciplinary, scientific field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health”, as defined by the American Medical Informatics Association (AMIA). As a subdiscipline, the medical and clinical informatics section focuses on the advancements in both methods and applications of informatics and information technology to improve the delivery of healthcare services.

This Special Issue aims to publish high-quality articles covering all fields of medical informatics and clinical informatics. If your paper is well prepared and approved for further publication, you might be eligible for discounts for your publication.

Dr. Jiang Bian
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • clinical decision support
  • mHealth and eHealth
  • clinical informatics
  • clinical research informatics
  • electronic health records
  • information technology
  • human factors
  • real-world data
  • real-world evidence
  • pragmatic clinical trials
  • implementation science
  • administrative and management systems
  • health information systems

Published Papers (4 papers)

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Research

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Article
Where Is My Mind (Looking at)? A Study of the EEG–Visual Attention Relationship
Informatics 2022, 9(1), 26; https://doi.org/10.3390/informatics9010026 - 09 Mar 2022
Viewed by 1281
Abstract
Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, deep learning, and medicine. One of the most common approaches to estimate a saliency map representing attention is based on the observed images. In this paper, [...] Read more.
Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, deep learning, and medicine. One of the most common approaches to estimate a saliency map representing attention is based on the observed images. In this paper, we show that visual attention can be retrieved from EEG acquisition. The results are comparable to traditional predictions from observed images, which is of great interest. Image-based saliency estimation being participant independent, the estimation from EEG could take into account the subject specificity. For this purpose, a set of signals has been recorded, and different models have been developed to study the relationship between visual attention and brain activity. The results are encouraging and comparable with other approaches estimating attention with other modalities. Being able to predict a visual saliency map from EEG could help in research studying the relationship between brain activity and visual attention. It could also help in various applications: vigilance assessment during driving, neuromarketing, and also in the help for the diagnosis and treatment of visual attention-related diseases. For the sake of reproducibility, the codes and dataset considered in this paper have been made publicly available to promote research in the field. Full article
(This article belongs to the Special Issue Feature Papers in Medical and Clinical Informatics)
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Article
Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques
Informatics 2022, 9(1), 4; https://doi.org/10.3390/informatics9010004 - 10 Jan 2022
Viewed by 1352
Abstract
Traumatic Brain Injury (TBI) is a devastating and life-threatening medical condition that can result in long-term physical and mental disabilities and even death. Early and accurate detection of Intracranial Hemorrhage (ICH) in TBI is crucial for analysis and treatment, as the condition can [...] Read more.
Traumatic Brain Injury (TBI) is a devastating and life-threatening medical condition that can result in long-term physical and mental disabilities and even death. Early and accurate detection of Intracranial Hemorrhage (ICH) in TBI is crucial for analysis and treatment, as the condition can deteriorate significantly with time. Hence, a rapid, reliable, and cost-effective computer-aided approach that can initially capture the hematoma features is highly relevant for real-time clinical diagnostics. In this study, the Gray Level Occurrence Matrix (GLCM), the Gray Level Run Length Matrix (GLRLM), and Hu moments are used to generate the texture features. The best set of discriminating features are obtained using various meta-heuristic algorithms, and these optimal features are subjected to different classifiers. The synthetic samples are generated using ADASYN to compensate for the data imbalance. The proposed CAD system attained 95.74% accuracy, 96.93% sensitivity, and 94.67% specificity using statistical and GLRLM features along with KNN classifier. Thus, the developed automated system can enhance the accuracy of hematoma detection, aid clinicians in the fast interpretation of CT images, and streamline triage workflow. Full article
(This article belongs to the Special Issue Feature Papers in Medical and Clinical Informatics)
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Review

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Review
Intelligent Remote Photoplethysmography-Based Methods for Heart Rate Estimation from Face Videos: A Survey
Informatics 2022, 9(3), 57; https://doi.org/10.3390/informatics9030057 - 07 Aug 2022
Viewed by 238
Abstract
Over the last few years, a rich amount of research has been conducted on remote vital sign monitoring of the human body. Remote photoplethysmography (rPPG) is a camera-based, unobtrusive technology that allows continuous monitoring of changes in vital signs and thereby helps to [...] Read more.
Over the last few years, a rich amount of research has been conducted on remote vital sign monitoring of the human body. Remote photoplethysmography (rPPG) is a camera-based, unobtrusive technology that allows continuous monitoring of changes in vital signs and thereby helps to diagnose and treat diseases earlier in an effective manner. Recent advances in computer vision and its extensive applications have led to rPPG being in high demand. This paper specifically presents a survey on different remote photoplethysmography methods and investigates all facets of heart rate analysis. We explore the investigation of the challenges of the video-based rPPG method and extend it to the recent advancements in the literature. We discuss the gap within the literature and suggestions for future directions. Full article
(This article belongs to the Special Issue Feature Papers in Medical and Clinical Informatics)
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Review
Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding
Informatics 2022, 9(2), 34; https://doi.org/10.3390/informatics9020034 - 18 Apr 2022
Viewed by 986
Abstract
The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child’s outcomes. In this regard, artificial intelligence (AI) [...] Read more.
The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child’s outcomes. In this regard, artificial intelligence (AI) can be used for the automatic analysis of fetal heart ultrasound images. This study reviews nondeep and deep learning approaches for assessing the fetal heart using standard four-chamber ultrasound images. The state-of-the-art techniques in the field are described and discussed. The compendium demonstrates the capability of automatic assessment of the fetal heart using AI technology. This work can serve as a resource for research in the field. Full article
(This article belongs to the Special Issue Feature Papers in Medical and Clinical Informatics)
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