• Journal of Korean Electronics
• /
• v.23 no.5
• /
• pp.5-16
• /
• 2003

• Journal of Korean Electronics
• /
• v.17 no.1
• /
• pp.92-96
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• 1997

• Journal of Korean Electronics
• /
• v.24 no.6
• /
• pp.26-26
• /
• 2004

• Journal of Korean Electronics
• /
• v.15 no.6
• /
• pp.1-7
• /
• 1995

• Journal of Korean Electronics
• /
• v.21 no.9
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• pp.10-15
• /
• 2001

• Journal of Korean Electronics
• /
• v.12 no.3
• /
• pp.5-6
• /
• 1992

• Quality Improvement in Health Care
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• v.4 no.1
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• pp.32-35
• /
• 1997

• Journal of Digital Convergence
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• v.10 no.2
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• pp.193-200
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• 2012

The existing EMR method placing computer servers in hospitals could expose patients' personal information to hospital officers and people for wrong purposes. In addition, if medical malpractice occurs, the possibility of distorting medical records might be higher because patients' medical records are stored in hospitals. This study provides an electronic medical record with a security system to solve patients' information disclosure. The electronic medical record system could be utilized as an important information when medical malpractice occurs. This system can provide higher security services certifying patients safely and efficiently as well as protecting patients' personal information.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.61-66
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• 2014

As a key technology of U-health, RFID can be applied to the hospitals in a variety of cases such as patient tracking, medical instrument management, and so on. However, adoption of RFID in healthcare does not reach expectations because of huge cost. Exact estimation of cost and effectiveness will boost adoption of RFID in healthcare. This study proposes a novel simulation technique to evaluate cost and effectiveness of RFID in hospital environment. To do this, this study proposes a technique for modeling patients' movements in a hospital. Based on the model, this study provides how to obtain tag event dataset by means of simulating identifications of RFID tags that are attached to patients.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1283-1292
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• 2022

At present, several artificial intelligence projects in the healthcare and medical field are competing with each other, and the interfaces between the systems lack unified specifications. Thus, this study presents an artificial intelligence platform for healthcare and medical fields which adopts the deep learning technology to provide algorithms, models and service support for the health and medical enterprise applications. The suggested platform can provide a large number of heterogeneous data processing, intelligent services, model managements, typical application scenarios, and other services for different types of business. In connection with the suggested platform application, we represents a medical service which is corresponding to the trusted and comprehensible tracking and analyzing patient behavior system for Health and Medical treatment using Internet of Behavior concept.