Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
Patient safety has become a growing concern in health care. The U.S. Institute of Medicine (IOM) report “To Err Is Human: Building a Safer Health System” in 1999 included estimations that medical error is the eighth leading cause of death in the United States and results in up to 100,000 deaths annually. However, many adverse events and errors occur in surgical practice. Within all kinds of surgical adverse events, wrong-side/wrong-site, wrong-procedure, and wrongpatient adverse events are the most devastating, unacceptable, and often result in litigation. Much literature claims that systems must be put in place to render it essentially impossible or at least extremely difficult for human error to cause harm to patients. Hence, this research aims to develop a prototype system based on active RFID that detects and prevents errors in the OR. To fully comprehend the operating room (OR) process, multiple rounds of on site discussions were conducted. IDEF0 models were subsequently constructed for identifying the opportunity of improvement and performing before-after analysis. Based on the analysis, the architecture of the proposed RFID-based OR system was developed. An on-site survey conducted subsequently for better understanding the hardware requirement will then be illustrated. Finally, an RFID-enhanced system based on both the proposed architecture and test results was developed for gaining better control and improving the safety level of the surgical operations.
dr._chuan-jun_su. 1970. \u201cModeling and Implementing RFID Enabled Operating Environment for Patient Safety Enhancement\u201d. Unknown Journal GJCST Volume 10 (GJCST Volume 10 Issue 10): .
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
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Patient safety has become a growing concern in health care. The U.S. Institute of Medicine (IOM) report “To Err Is Human: Building a Safer Health System” in 1999 included estimations that medical error is the eighth leading cause of death in the United States and results in up to 100,000 deaths annually. However, many adverse events and errors occur in surgical practice. Within all kinds of surgical adverse events, wrong-side/wrong-site, wrong-procedure, and wrongpatient adverse events are the most devastating, unacceptable, and often result in litigation. Much literature claims that systems must be put in place to render it essentially impossible or at least extremely difficult for human error to cause harm to patients. Hence, this research aims to develop a prototype system based on active RFID that detects and prevents errors in the OR. To fully comprehend the operating room (OR) process, multiple rounds of on site discussions were conducted. IDEF0 models were subsequently constructed for identifying the opportunity of improvement and performing before-after analysis. Based on the analysis, the architecture of the proposed RFID-based OR system was developed. An on-site survey conducted subsequently for better understanding the hardware requirement will then be illustrated. Finally, an RFID-enhanced system based on both the proposed architecture and test results was developed for gaining better control and improving the safety level of the surgical operations.
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