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Songpu Li, Xinran Yu and Peng Chen
Model robustness is an important index in medical cybersecurity, and hard-negative samples in electronic medical records can provide more gradient information, which can effectively improve the robustness of a model. However, hard negatives pose difficul...
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Salvatore Calcagno, Andrea Calvagna, Emiliano Tramontana and Gabriella Verga
The Electronic Health Record (EHR) is a system for collecting and storing patient medical records as data that can be mechanically accessed, hence facilitating and assisting the medical decision-making process. EHRs exist in several formats, and each for...
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Xiaonan Si, Lei Wang, Wenchang Xu, Biao Wang and Wenbo Cheng
Gout is one of the most painful diseases in the world. Accurate classification of gout is crucial for diagnosis and treatment which can potentially save lives. However, the current methods for classifying gout periods have demonstrated poor performance a...
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Bronwin Patrickson, Mike Musker, Dan Thorpe, Yasmin van Kasteren, Niranjan Bidargaddi and The Consumer and Carer Advisory Group (CCAG)
Advancements in digital monitoring solutions collaborate closely with electronic medical records. These fine-grained monitoring capacities can generate and process extensive electronic record data. Such capacities promise to enhance mental health care bu...
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Alessia Paglialonga, Rebecca Theal, Bruce Knox, Robert Kyba, David Barber, Aziz Guergachi and Karim Keshavjee
The aim of this study was to design a virtual peer-to-peer intervention for patients with type 2 diabetes (T2D) by grouping patients from specific segments using data from primary care electronic medical records (EMRs). Two opposing segments were identif...
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Xiaohui Cui, Yu Yang, Dongmei Li, Xiaolong Qu, Lei Yao, Sisi Luo and Chao Song
Recently, researchers have extensively explored various methods for electronic medical record named entity recognition, including character-based, word-based, and hybrid methods. Nonetheless, these methods frequently disregard the semantic context of ent...
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Rowa Aljondi, Salem Saeed Alghamdi, Abdulrahman Tajaldeen, Shareefah Alassiri, Monagi H. Alkinani and Thomas Bertinotti
Background: Breast cancer has a 14.8% incidence rate and an 8.5% fatality rate in Saudi Arabia. Mammography is useful for the early detection of breast cancer. Researchers have been developing artificial intelligence (AI) algorithms for early breast canc...
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Shefa M. Tawalbeh, Ahmed Al-Omari, Lina M. K. Al-Ebbini and Hiam Alquran
Jordanian healthcare institutes have launched several programs since 2009 to establish health information systems (HISs). Nowadays, the generic expectation is that the use of HIS resources is performed on daily basis among healthcare staff. However, ther...
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Ruhi Kiran Bajaj, Rebecca Mary Meiring and Fernando Beltran
Computational analysis and integration of smartwatch data with Electronic Medical Records (EMR) present potential uses in preventing, diagnosing, and managing chronic diseases. One of the key requirements for the successful clinical application of smartw...
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Frances Heredia-Negron, Natalie Alamo-Rodriguez, Lenamari Oyola-Velazquez, Brenda Nieves, Kelvin Carrasquillo, Harry Hochheiser, Brian Fristensky, Istoni Daluz-Santana, Emma Fernandez-Repollet and Abiel Roche-Lima
Artificial intelligence (AI) and machine learning (ML) facilitate the creation of revolutionary medical techniques. Unfortunately, biases in current AI and ML approaches are perpetuating minority health inequity. One of the strategies to solve this probl...
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