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Ashok Suragala, Gurugubelli Sai Dilip Kumar, Sri Karthik Avala
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- Assistant Professor, Student, Student, Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Gurajada, Vizianagaram, Department of Mechanical Engineering, Andhra University College of Engineering, Visakhapatnam, Department of Computer Science & Engineering, VIT Chennai University, Chennai, Andhra Pradesh, Andhra Pradesh, Tamil Nadu, India, India, India
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Abstract
nTube misplacement can lead to complications in patients together with serious medical malpractice cases. Intubation and the insertion of various medical tubes were employed to safeguard the airways of critically ill patients. Critically unwell patients underwent intubation, with the insertion of various medical tubes to safeguard their airways. The Nasogastric tube (NGT) serves the purpose of providing nutrition, while the Central Venous Catheter (CVC) finds application in a range of medical procedures. The significant challenge lies in doctors adhering to medical protocols to ensure the correct installation of these tubes. The implementation of medical protocols by physicians to guarantee the correct placement of tubes presents a significant challenge. Misplaced tubes increase the probability of complications in patients and, in the worst of cases, even lead to mortality. So, identifying the proper positioning of tubes before starting the procedure is crucial. In this paper, we propose identifying the misplaced tube and catheters detection using deep learning approach with accurate outcome.
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Keywords: Tube Misalignment, Efficient net B7, Central Venous Catheter, deep learning, Nasogastric tube, EfficientNet model
n[if 424 equals=”Regular Issue”][This article belongs to International Journal of Computer Science Languages(ijcsl)]
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References
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| Volume | 01 |
| Issue | 02 |
| Received | August 28, 2023 |
| Accepted | October 9, 2023 |
| Published | October 30, 2023 |
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