Objectives: To investigate the feasibility analysis of predicting the pathological differentiation grade of breast invasive ductal carcinoma based on DCE-MRI imaging histology. Methodology: 198 ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Abstract: Kubeflow is a global machine learning platform that is open-source in nature. Its primary objective is to streamline the process of deploying, managing, and scaling machine learning (ML) and ...
Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...
Pulmonary hypertension in CKD is frequently underdiagnosed due to nonspecific early symptoms and limited screening practices. A machine learning model using basic clinical data can predict PH risk, ...
In this tutorial, we explore LitServe, a lightweight and powerful serving framework that allows us to deploy machine learning models as APIs with minimal effort. We build and test multiple endpoints ...
A simple Flask application that can serve predictions machine learning model. Reads a pickled sklearn model into memory when the Flask app is started and returns predictions through the /predict ...
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1 Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia 2 InnoV'COM Laboratory-Sup'Com, University of Carthage, Ariana, Tunisia ...
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