… studies, we propose a machine learning-based framework to identify cases and controls in
… our framework through Chinese EHR data, and the experimental results show our framework …

… In this article, researchers propose a machine learning-based framework for detection of
COVID-19 from X-ray images. We used one traditional machine learning approach, LR, which is …

… Machine learning-based framework for battery lifetime prediction In this section, a comprehensive
ML-based framework is … Three main modules constitute the structure of the framework, …

… Machine learning has been extensively applied for traffic classification and intrusion detection.
In this paper, we propose a framework, … network edge, this framework extracts features per …

… In this manuscript, the authors propose an IoT and interpretable deep transfer learning-based
framework, ‘Automatic and Intelligent Data Collector and Classifier’ (AIDCC), for the …

… on grid or random search [5] and TPOT which is based on genetic programming [10]. …
learningbased framework for automated selection and hyperparameter tuning for machine learning …

… framework is capable of generating matching geometric patterns for a targeted response
through a databank constructed from our machine learning … machine-learning based framework …

… prediction model through machine learning. Machine learning outperforms conventional …
Our purpose is to use machine learning to analyze the data of 304,145 physical examinees, …

… In this work, we put forward inTIME, a machine learning-based integrated framework that
provides an holistic view in the cyber-threat intelligence process and allows security analysts to …

In this paper we propose a distributed architecture to provide machine learning practitioners
with a set of tools and cloud services that cover the whole machine learning development …