AIMC Topic: Machine Learning

Clear Filters Showing 17721 to 17730 of 34417 articles

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.

BMJ (Clinical research ed.)
OBJECTIVE: To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties.

Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Early unplanned hospital readmissions are associated with increased harm to patients, increased medical costs, and negative hospital reputation. With the identification of at-risk patients, a crucial step toward improving care, appropriat...

Fast activation maximization for molecular sequence design.

BMC bioinformatics
BACKGROUND: Optimization of DNA and protein sequences based on Machine Learning models is becoming a powerful tool for molecular design. Activation maximization offers a simple design strategy for differentiable models: one-hot coded sequences are fi...

Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis.

Radiology
Background Advances in computer processing and improvements in data availability have led to the development of machine learning (ML) techniques for mammographic imaging. Purpose To evaluate the reported performance of stand-alone ML applications for...

Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?

NeuroImage
Cognitive performance can be predicted from an individual's functional brain connectivity with modest accuracy using machine learning approaches. As yet, however, predictive models have arguably yielded limited insight into the neurobiological proces...

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

IEEE transactions on bio-medical engineering
OBJECTIVES: Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used sup...

Application of Machine Learning to Predict Dielectric Properties of In Vivo Biological Tissue.

Sensors (Basel, Switzerland)
In this paper we revisited a database with measurements of the dielectric properties of rat muscles. Measurements were performed both in vivo and ex vivo; the latter were performed in tissues with varying levels of hydration. Dielectric property meas...

Novel Prediction of Diagnosis Effectiveness for Adaptation of the Spectral Kurtosis Technology to Varying Operating Conditions.

Sensors (Basel, Switzerland)
In this paper, two novel consistency vectors are proposed, which when combined with appropriate machine learning algorithms, can be used to adapt the Spectral Kurtosis technology for optimum gearbox damage diagnosis in varying operating conditions. M...

Impact of Factors of Online Deceptive Reviews on Customer Purchase Decision Based on Machine Learning.

Journal of healthcare engineering
Online deceptive reviews widely exist in the online shopping environment. Numerous studies have investigated the impact of online product reviews on customer behaviour and sales. However, the existing literature is mainly based on real product review...