ascopubs.org

Simple Linear Cancer Risk Prediction Models With Novel Features Outperform Complex Approaches

Methodological Comparison of Mapping the Expanded Prostate Cancer Index Composite to EuroQoL-5D-3L Using Cross-Sectional and Longitudinal Data: Secondary Analysis of NRG/RTOG 0415 The ability to ...
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 considerable interest among researchers. The debate around the use of machine ...
Electronic Design

Modeling on Mondays: SPICE Modeling of Common Active Devices—An Overview (Part 1)

A variety of linear models are available to represent common active electronic devices such as transistors and vacuum tubes. Devices operating under large-signal conditions often require nonlinear ...
Labroots

Log-linear Model for Modeling for Biases in Microbiome Studies

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If ...
techtimes

The Role of Assumptions in Statistical Model Selection

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
Machine Design

Modeling and Optimization of Linear Machines Using FEA

Already registered? Click here to login now. Linear electromagnetic devices — such as linear motors, generators, actuators, and magnetic gears — play a vital role in precision motion control, energy ...