ỨNG DỤNG OTOMAT HỮU HẠN CHO HỆ THỐNG Y TẾ KHÁM BỆNH KHÔNG TIẾP XÚC DỰA TRÊN TRIỆU CHỨNG LÂM SÀNG

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Tác giả: Hong Quang Doan, Hong Minh Le, Hai Binh Nguyen, Huy Cong Nguyen, Huy Khan Nguyen, Thi Thuy Nguyen, Van Hiep Tran, Ban Vu, Minh Thoai Vu, Xuan Manh Vu

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học và Công nghệ Năng lượng, 2023

Mô tả vật lý: tr.28

Bộ sưu tập: Metadata

ID: 345407

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An engine was developed based on the mathematical model of Non-Deterministic Finite Automata (NFA) to classify non-contact medical examinations according to patients' clinical symptoms. The input data used to build the engine consists of a collection of patients' clinical symptoms, hospital examination streams, and a set of rules for classifying medical examinations based on clinical symptoms. The engine was trained using a dataset collected from the medical records of patients with different clinical symptoms from a central hospital, a district general hospital, and a provincial medical center, totaling approximately 50,000 registrations. This engine has been integrated into the "Contactless Patient Streaming and Examination Registration System" to streamline medicalexaminations during the Covid-19 pandemic in central and local hospitals. The system enables patients to register, queue online, and be automatically streamed based on the clinical symptoms declared by the patients. The mathematical model used to build the engine was studied, tested, analyzed, evaluated, and compared with other mathematical models. Comprehensive analysis results demonstrate that NFA is the most suitable model for engine development. After integrating the engine into the system, it was tested on a dataset that randomly selected values 100 times from the set of symptoms in the patient medical record database. The result yielded an accuracy of approximately 80.5%.Một engine được xây dựng dựa trên mô hình toán học của otomat hữu hạn không đơn định (NFA) để phân luồng khám bệnh không tiếp xúc theo triệu chứng lâm sàng (sau đây gọi là “triệu chứng”). Trong đó, dữ liệu đầu vào để xây dựng engine là tập hợp các triệu chứng lâm sàng của người bệnh
tập hợp các luồng khám bệnh của bệnh viện và bộ quy tắc phân luồng khám bệnh theo triệu chứng lâm sàng. Engine được huấn luyện bằng bộ dữ liệu thu thập được từ hồ sơ đăng ký khám bệnh của bệnh nhân với các triệu chứng lâm sàng khác nhau từ một bệnh viện tuyến trung ương, một bệnh viện đa khoa cấp tỉnh và một trung tâm y tế cấp huyện với tổng số lượt đăng ký khám xấp xỉ 50.000 lượt. Engine này đã được tích hợp vào “Hệ thống đăng ký khám và phân luồng bệnh nhân không tiếp xúc” để phân luồng khám bệnh trong mùa dịch Covid-19 tại một số bệnh viện tuyến trung ương và địa phương. Hệ thống này cho phép bệnh nhân đăng ký, xếp hàng trực tuyến (online) và được tự động phân luồng khám thông qua các triệu chứng lâm sàng mà bệnh nhân khai báo. Mô hình toán học để xây dựng engine cũng được nghiên cứu, thử nghiệm, phân tích và đánh giá với một số các mô hình toán học khác. Kết quả phân tích toàn diện cho thấy NFA là mô hình hợp lý nhất cho việc phát triển engine. Hệ thống sau khi tích hợp với engine được thử nghiệm với bộ dữ liệu lấy ngẫu nhiên 100 lần từ tập hợp các triệu chứng trong kho hồ sơ bệnh nhân. Kết quả cho ra trùng khớp 80,5%

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