AIMC Topic: Choice Behavior
Clear Filters Showing 41 to 50 of 51 articles
Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries.
BMC public health
May 29, 2025
INTRODUCTION: Informed contraceptive choice is declared when a woman selects a methods of contraceptive after receiving comprehensive information on available alternatives, side effects, and management if adverse effect happens. Access to contracepti...
The robotic companion's choice encourages sustainable food choices: The moderating role of anthropomorphism.
Applied psychology. Health and well-being
May 1, 2025
Previous research has shown the impact of the food choices of others on individuals' own food choices. We conducted two studies to investigate how a robot's choice might influence people's choices between meat-heavy and vegetable-forward meals in ima...
Inverting Cognitive Models With Neural Networks to Infer Preferences From Fixations.
Cognitive science
Nov 1, 2024
Inferring an individual's preferences from their observable behavior is a key step in the development of assistive decision-making technology. Although machine learning models such as neural networks could in principle be deployed toward this inferen...
MedDietAgent: An AI-based Mobile App for Harmonizing Individuals' Dietary Choices with the Mediterranean Diet Pattern.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Recently, there has been an increasing interest in applying technological advances to offer specific dietary recommendations in the field of nutrition and health. Dietary recommendation systems are advanced tools designed to assist individuals in mak...
Using large-scale experiments and machine learning to discover theories of human decision-making.
Science (New York, N.Y.)
Jun 11, 2021
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this go...
Categorization of digitized artworks by media with brain programming.
Applied optics
May 10, 2020
This work describes the use of brain programming applied to the categorization problem of art media. The art categorization problem-from the standpoint of materials and techniques used by artists-presents a challenging task and is considered an open ...
The Effectiveness of the Game of Dice Task in Predicting At-Risk and Problem Gambling Among Adolescents: The Contribution of the Neural Networks.
Journal of gambling studies
Mar 1, 2019
The Game of Dice Task (GDT; Brand et al. in Neuropsychology 19:267-277, 2005a; Psychiatry Res 133:91-99, 2005b) measures decision-making under objective risk conditions. Although disadvantageous decision-making has been shown in individuals with subs...
Predicting similarity judgments in intertemporal choice with machine learning.
Psychonomic bulletin & review
Apr 1, 2018
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 promise of cyborg intelligence.
Learning & behavior
Mar 1, 2017
Yu et al. (2016) demonstrated that algorithms designed to find efficient routes in standard mazes can be integrated with the natural processes controlling rat navigation and spatial choices, and they pointed out the promise of such "cyborg intelligen...
A hierarchical two-phase framework for selecting genes in cancer datasets with a neuro-fuzzy system.
Technology and health care : official journal of the European Society for Engineering and Medicine
Apr 29, 2016
Finding the minimum number of appropriate biomarkers for specific targets such as a lung cancer has been a challenging issue in bioinformatics. We propose a hierarchical two-phase framework for selecting appropriate biomarkers that extracts candidate...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823