… The subjects were randomly divided into a training set (80%) and a test set (20%). Multivariable
logistic regression … models were constructed using the four machine learning methods (…

… Machine learning to predict occult nodal … logistic regression, and a nomogram model was
constructed based on the influencing factors. The discrimination of the nomo⁃ gram model was …

… ) algorithm combined with machine learning model in the evaluation … The logistic regression
was established in the datum sets … forest model has a high application value in the prognosis …

… With the development of imaging technology and machine learning methods, multi-modal
image … of machine learning and multi-modal imaging in the clinical diagnosis and prognosis of …

… developing more interpretable deep learning systems (DLS) … [35] developed a DLS to predict
visual prognosis. The system … , but many people actually have multiple eye diseases. What’…

… irradiation are independent prognostic factors affecting the … multiple model fusion including
the defect detection by multi-… DDML with an automatic machine learning method achieves the …

… The research subjects were mainly elderly people. The … regression model and machine
learning. The … Conclusions:The models included in this study have good prediction,but the …

… 任务线性回归模型 (multi-task logistic regression,MTLR)[8].Fotso … DeepHit:a deep learning
approach to survival analysis with … The SUPPORT prognostic model:objective estimates of sur…

… a prognostic prediction model for diffuse large B-cell lymphoma.… machine learning algorithms
to identify groups of subjects … tree and LCA by the logistic regression. In each leaf node of …

… of immunotherapy prediction models and provided new … CT Provide a predictive machine
learning model that could be … of a multivariable prediction model for individual prognosis or …