The rapid advances in mobile computing technology have the potential to change the way radiology and medicine as a whole are practiced. Several mobile computing advances have not yet found application to the practice of radiology, while others have already been applied to radiology but are not in widespread clinical use. This review addresses several areas where radiology and medicine in general may benefit from adoption of the latest mobile computing technologies and speculates on potential future applications.
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http://dx.doi.org/10.1016/j.acra.2013.09.009 | DOI Listing |
BMC Med Inform Decis Mak
December 2024
Fakher Mechatronic Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Background: Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Mobile technologies enable Parkinson's patients to improve their quality of life, manage symptoms, and enhance overall well-being through various applications (apps). There is no integrated list of specific capabilities available to cater to the unique needs of Parkinson's patient-focused mobile apps.
View Article and Find Full Text PDFJMIR Aging
December 2024
Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.
Background: There are numerous communication barriers between family caregivers and providers of people living with dementia, which can pose challenges to caregiving and clinical decision-making. To address these barriers, a new web and mobile-enabled app, called CareHeroes, was developed, which promotes the collection and secured sharing of clinical information between caregivers and providers. It also provides caregiver support and education.
View Article and Find Full Text PDFInfect Dis Model
March 2025
Artificial Intelligence & Mathematical Modeling Lab (AIMM Lab), Dalla Lana School of Public Health, University of Toronto, 155 College St Room 500, Toronto, ON, M5T 3M7, Canada.
Acute flaccid paralysis (AFP) case surveillance is pivotal for the early detection of potential poliovirus, particularly in endemic countries such as Ethiopia. The community-based surveillance system implemented in Ethiopia has significantly improved AFP surveillance. However, challenges like delayed detection and disorganized communication persist.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Background: Wearable technologies have become increasingly prominent in health care. However, intricate machine learning and deep learning algorithms often lead to the development of "black box" models, which lack transparency and comprehensibility for medical professionals and end users. In this context, the integration of explainable artificial intelligence (XAI) has emerged as a crucial solution.
View Article and Find Full Text PDFJMIR Biomed Eng
December 2024
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States.
Background: Cell concentration in body fluid is an important factor for clinical diagnosis. The traditional method involves clinicians manually counting cells under microscopes, which is labor-intensive. Automated cell concentration estimation can be achieved using flow cytometers; however, their high cost limits accessibility.
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