Machine learning aided tumor diagnosis / 肿瘤

In recent years, the application of high-quality digital slides in pathological diagnosis has changed the traditional reading methods. As a result, a large number of quantitative analysis algorithms come into being. Among them, the machine deep learning algorithm has outperformed other algorithms in the analysis of large data, showing great potential in the analysis of pathological sections. The process of pathological image analysis based on machine learning consists of feature extraction and classification to determine the nature, grading and prognosis of tumors, which can improve the objectivity and accuracy of pathological diagnosis. At present, those fields in which machine learning aided pathological image analysis presents as a relatively mature diagnostic tool include the diagnosis and prognosis of breast cancer, the determination of the nature of skin cancer, the diagnosis and prognosis of lung cancer, and the grading of prostate cancer and cervical intraepithelial neoplasia. In this paper, the research progresses in these fields are reviewed and discussed.

Evaluation on the Service Quality of Domestic Famous Mobile Medical App / 医学信息学杂志

The paper selects 10 mobile medical App with relatively large influence in the industry,evaluates the data about quality of inquiry service and overall quality of these App in accordance with the information provided on the interface,and meanwhile analyzes the trend of downloading App by people.