Đánh giá hệ thống về vai trò của Học sâu trong việc phát hiện ung thư túi mật qua hình ảnh CT

Abhishek Sehrawat1,2, Varun P. Gopi3, Anita Gupta2
1Department of Radiodiagnosis and Imaging, All India Institute of Medical Sciences Bhopal, Bhopal, India
2 Chitkara School of Health Sciences , Chitkara University, Rajpura, India
3Department of ECE, NIT Tiruchirappalli, Tiruchirappalli, India

Tóm tắt

Ung thư túi mật (GBC) là một căn bệnh thách thức và thường dẫn đến tử vong, với việc phát hiện sớm đóng vai trò quan trọng trong việc cải thiện kết quả điều trị cho bệnh nhân. Bài đánh giá hệ thống này khám phá vai trò của Trí tuệ nhân tạo Học sâu (Deep Learning AI) trong chẩn đoán ung thư túi mật bằng cách sử dụng hình ảnh chụp cắt lớp vi tính (CT). Một tìm kiếm toàn diện đã được thực hiện qua nhiều cơ sở dữ liệu điện tử để tìm kiếm các nghiên cứu phù hợp được công bố đến tháng 8 năm 2023. Các nghiên cứu sử dụng các thuật toán AI để phân tích hình ảnh CT trong bối cảnh phát hiện ung thư túi mật đã được đưa vào. Việc thu thập dữ liệu và đánh giá chất lượng đã được thực hiện một cách hệ thống. Đánh giá đã xác định được 30 nghiên cứu cho thấy việc ứng dụng ngày càng tăng của AI trong việc phát hiện sớm ung thư túi mật thông qua hình ảnh CT. Những nghiên cứu này đã chứng minh những kết quả hứa hẹn về độ nhạy và độ đặc hiệu, với một số nghiên cứu đạt hiệu suất chẩn đoán tương đương hoặc thậm chí vượt qua các bác sĩ chuyên khoa có kinh nghiệm. Hơn nữa, việc tích hợp các công cụ do AI điều khiển đã cho thấy tiềm năng trong việc cải thiện hiệu suất và giảm tải công việc cho các chuyên gia chăm sóc sức khỏe. Trí tuệ nhân tạo Học sâu có tiềm năng cải thiện phát hiện sớm ung thư túi mật thông qua phân tích hình ảnh CT. Bài đánh giá hệ thống này làm nổi bật tiềm năng của AI trong việc nâng cao độ chính xác và hiệu quả chẩn đoán. Cần có thêm nghiên cứu và xác thực để khai thác đầy đủ lợi ích lâm sàng của AI trong bối cảnh này.

Từ khóa

#ung thư túi mật #chẩn đoán #trí tuệ nhân tạo #học sâu #hình ảnh CT

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