Health Monitoring in the Context of Medical Big Data

Topic Information

Dear Colleagues,

The rise of medical big data has brought unprecedented opportunities and challenges for health monitoring. A series of recent studies has revealed the crucial role of big data in understanding service patterns, assessing intervention effectiveness, and identifying health disparities. First, big data analytics can accurately reveal disparities in service accessibility and clinical outcomes. For example, research has found that mental health services delivered solely by telephone are more prevalent among the elderly and vulnerable populations. Simultaneously, patients in rural and remote areas receive less access to video telemedicine services compared to urban patients, highlighting the existence of a “digital divide” in specific populations. These findings rely on correlation analysis of large-scale electronic health records (EMRs) and administrative data, demonstrating big data’s ability to monitor health equity. Second, big data is driving the integration and evaluation of new technologies such as telemedicine and artificial intelligence. Artificial intelligence is being widely applied to sleep analysis (e.g., insomnia, sleep apnea), wearable device data analysis, disease diagnosis, and remote mental health services, foreshadowing a more intelligent and continuous health monitoring future.

In summary, medical big data is profoundly transforming the model of health monitoring. This Topic is open to innovative studies that explore the application of big data to continuously optimize telemedicine deployment to narrow service gaps; integrate artificial intelligence into clinical monitoring and decision support systems; and build a more comprehensive, equitable, and dynamic individual and population health monitoring system by improving the interoperability, accuracy, and representativeness of multi-source data. However, challenges such as data bias, algorithmic fairness, and privacy protection must also be considered.

Dr. Javad Razjouyan
Dr. Julianna B. D. Hogan
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Clinics and Practice clinpract	2.2	2.8	2011	25.7 Days	CHF 1800	Submit
Digital digital	-	4.8	2021	27.7 Days	CHF 1200	Submit
Healthcare healthcare	2.7	4.7	2013	22.4 Days	CHF 2700	Submit
Information information	2.9	6.5	2010	20.9 Days	CHF 1800	Submit
Mathematical and Computational Applications mca	2.1	-	1996	24.9 Days	CHF 1600	Submit
Sci sci	-	5.2	2019	26.7 Days	CHF 1400	Submit

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