The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
IEEE

Magneto Inductive (MI) Channel Variables Prediction Through Machine Learning Linear Regression Method, for Underwater and Underground WSNs

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...
UroToday

Predicting PSA50 response to [Formula: see text]Lu-PSMA therapy using machine learning and automated total tumor volume.

The 177Lu-PSMA therapy is an established treatment for metastatic castration-resistant prostate cancer (mCRPC), targeting the prostate-specific membrane antigen (PSMA). Despite well-established ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Hosted on MSN

Complete | What Is Linear Regression Machine Learning

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...
C&EN

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...
IEEE

Systematic Bias of Machine Learning Regression Models and Correction

Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...
Frontiers

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.