人工智能於醫療場域的應用—以某醫學中心為例

The Application of Artificial Intelligence in Medical Service: Take a Medical Center as an Example

10.6530/YYN.202103_15(1).0003

方文輝(W.H Fang)；林錦生(Chin-Sheng Lin)；林嶔(Chin Lin)；李家政(Chia-Cheng Lee)

人工智慧 ； 無監督學習 ； 醫療決策輔助 ； artificial intelligence ； unsupervised transfer feature learning ； Medical decision support

源遠護理

15卷1期（2021 / 03 / 01）

16 - 22

繁體中文

隨著人工智慧演算法的推陳出新，其在醫療場域的應應也日趨多元，例如：淋巴結轉移檢查、糖尿病視網膜病變檢測、皮膚癌偵測及肺炎檢測等，某醫學中心人工智慧暨物聯網研究團隊陸續利用無監督式的轉移特徵學習，應用於心電圖預測血鉀及心肌梗塞上，獲得良好成效；這不單單只是為學術研究發表，更進一步落實應用在醫療場域，以人工智慧輔助醫療決策與診斷，早期預測警示病人異常變化，提昇病人安全，著實印證醫療照護人工智慧化。

With the advance of artificial intelligence algorithms, their applications in the medical field have become increasingly diverse, such as lymph node metastasis detection, diabetic retinopathy detection, skin cancer detection and pneumonia detection, etc., The research team of Artificial Intelligence of Things in a Medical Center has successively used ECG to predict serum potassium and myocardial infarction via unsupervised transfer feature learning and achieved good results. The above-mentioned research is not only published as academic research, but is further implemented and applied in the medical field, confirming the artificial intelligence of medical care.

1. Cahan, A.,Cimino, J. J.(2017).A Learning Health Care System Using Computer-Aided Diagnosis.J Med Internet Res,19(3),e54.
2. Ehteshami Bejnordi, B.,Veta, M.,Johannes van Diest, P.,van Ginneken, B.,Karssemeijer, N.,Litjens, G.,Venancio, R.(2017).Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.Jama,318(22),2199-2210.
3. Esteva, A.,Kuprel, B.,Novoa, R. A.,Ko, J.,Swetter, S. M.,Blau, H. M.,Thrun, S.(2017).Dermatologist-level classification of skin cancer with deep neural networks.Nature,542(7639),115-118.
4. Grewal, M.,Srivastava, M. M.,Kumar, P.,Varadarajan, S.(2017).,未出版
5. Gulshan, V.,Peng, L.,Coram, M.,Stumpe, M. C.,Wu, D.,Narayanaswamy, A.,Webster, D. R.(2016).Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.Jama,316(22),2402-2410.
6. He, K.,Zhang, X.,Ren, S.,Sun, J.(2016).Deep residual learning for image recognition.Proceedings of the IEEE conference on computer vision and pattern recognition
7. Krizhevsky, A.,Sutskever, I.,Hinton, G. E.(2012).Imagenet classification with deep convolutional neural networks.Advances in neural information processing systems
8. Litjens, G.,Kooi, T.,Bejnordi, B. E.,Setio, A. A. A.,Ciompi, F.,Ghafoorian, M.,Sanchez, C. I.(2017).A survey on deep learning in medical image analysis.Med Image Anal,42,60-88.
9. Rajpurkar, P.,Irvin, J.,Zhu, K.,Yang, B.,Mehta, H.,Duan, T.,Shpanskaya, K.(2017).,未出版
10. Shie, C.-K.,Chuang, C.-H.,Chou, C.-N.,Wu, M.-H.,Chang, E. Y.(2015).Transfer representation learning for medical image analysis.Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE

1. (2024)。AI時代自主健康管理之實踐。管理資訊計算，13(2)，95-110。