{"title":"Medical Instruments Whereabouts Using Artificial Intelligence","authors":"Ms. Aishwarya Gowda A G, Hui-Kai Su, W. Kuo","doi":"10.1109/ComPE53109.2021.9752235","DOIUrl":null,"url":null,"abstract":"In the growing requirement of healthcare needs the healthcare devices and instruments are used in every level of treatments. All of these devices are not just used once in their lifetime. Most of the devices are very expensive and are reused on different patients depending on their requirements. As the reusing increases, the history of usage and disinfecting with proper cleaning plays a major role in maintaining hygiene. This process of maintaining the required hygiene will stop the spread of diseases and infections to other patients. Hence, knowing the complete whereabouts of medical instruments will ensure the safety and provide complete information about the devices at a single tap before using the device. This gives a clear understanding of the devices for doctors or health care workers before the use of any reusable medical instruments. The process of recording the whereabouts of these instruments is accomplished with the latest striving technology like Artificial Intelligence. This will not just help in knowing the history but also provides clarity of information and trust on the devices before being used. LSTM is a model based on artificial intelligence which adds on in detecting the device and the purpose of usage automatically. The whereabouts are identified and carried out with a well-trained AI model and additive real-time data updates.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Performance Evaluation (ComPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComPE53109.2021.9752235","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In the growing requirement of healthcare needs the healthcare devices and instruments are used in every level of treatments. All of these devices are not just used once in their lifetime. Most of the devices are very expensive and are reused on different patients depending on their requirements. As the reusing increases, the history of usage and disinfecting with proper cleaning plays a major role in maintaining hygiene. This process of maintaining the required hygiene will stop the spread of diseases and infections to other patients. Hence, knowing the complete whereabouts of medical instruments will ensure the safety and provide complete information about the devices at a single tap before using the device. This gives a clear understanding of the devices for doctors or health care workers before the use of any reusable medical instruments. The process of recording the whereabouts of these instruments is accomplished with the latest striving technology like Artificial Intelligence. This will not just help in knowing the history but also provides clarity of information and trust on the devices before being used. LSTM is a model based on artificial intelligence which adds on in detecting the device and the purpose of usage automatically. The whereabouts are identified and carried out with a well-trained AI model and additive real-time data updates.