AIMC Topic: Decision Making

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Personalized Pancreatic Cancer Management: A Systematic Review of How Machine Learning Is Supporting Decision-making.

Pancreas
This review critically analyzes how machine learning is being used to support clinical decision-making in the management of potentially resectable pancreatic cancer. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses...

Enhanced Error Decoding from Error-Related Potentials using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Error-related potentials are considered an important neuro-correlate for monitoring human intentionality in decision-making, human-human, or human-machine interaction scenarios. Multiple methods have been proposed in order to improve the recognition ...

A Preventive Model for Muscle Injuries: A Novel Approach based on Learning Algorithms.

Medicine and science in sports and exercise
INTRODUCTION: The application of contemporary statistical approaches coming from Machine Learning and Data Mining environments to build more robust predictive models to identify athletes at high risk for injury might support injury prevention strateg...

Opportunities and obstacles for deep learning in biology and medicine.

Journal of the Royal Society, Interface
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine ar...

Predicting similarity judgments in intertemporal choice with machine learning.

Psychonomic bulletin & review
Similarity models of intertemporal choice are heuristics that choose based on similarity judgments of the reward amounts and time delays. Yet, we do not know how these judgments are made. Here, we use machine-learning algorithms to assess what factor...

The role of (bounded) optimization in theory testing and prediction.

The Behavioral and brain sciences
We argue that a radically increased emphasis on (bounded) optimality can contribute to cognitive science by supporting prediction. Bounded optimality (computational rationality), an idea that borrowed from artificial intelligence, supports a priori b...

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study so...