Thông tin tài liệu
Nhan đề : | Detection and explanation of anomalies in healthcare data |
Tác giả : | Durgesh, Samariya Jiangang, Ma Sunil, Aryal |
Năm xuất bản : | 2023 |
Nhà xuất bản : | Springer |
Tóm tắt : | The growth of databases in the healthcare domain opens multiple doors for machine learning and artificial intelligence technology. Many medical devices are available in the medical field; however, medical errors remain a severe challenge. Different algorithms are developed to identify and solve medical errors, such as detecting anomalous readings, anomalous health conditions of a patient, etc. However, they fail to answer why those entries are considered an anomaly. This research gap leads to an outlying aspect mining problem. |
Mô tả: | CC BY |
URI: | https://link.springer.com/article/10.1007/s13755-023-00221-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7670 |
Bộ sưu tập | OER - Công nghệ thông tin |
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