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Predictive Modelling for Heart Disease Risk Assessment Using Logistic Regression in Machine Learning
Abstract: Worldwide, cardiovascular disease has remained one of the topmost killers among all diseases. This has stirred a high interest in prognostic models with early detection and prevention ...
This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...
Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...
Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...
Objective: To extract and analyze the image features of two-dimensional ultrasound images and elastic images of four thyroid nodules by radiomics, and then further convolution processing to construct ...
Abstract: Lung cancer remains one of the most important issues related to cancer mortality worldwide due to the late diagnosis and the need for invasive biopsy procedures. There has emerged a new and ...
Artificial intelligence (AI) is transforming the energy sector, helping power plant operators optimize efficiency, reduce emissions, and prevent costly equipment failures. By analyzing vast amounts of ...
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