Is cognitive learning a machine learning?
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| Papers (8) | Insight |
|---|---|
20 Aug 2017 45 Citations | Our results suggest that machine learning is a potentially powerful tool to model and understand brain activities. |
49 Citations | The current study results reveal that machine learning techniques can accurately classify cognitive impairment and reduce the number of measures required for diagnosis. |
13 Citations | We suggest that continued applications will allow cognitive researchers the ability to model the complex real-world problems where machine learning has recently been successful, providing more complete behavioural descriptions. |
25 Citations | Overall, the paper concludes that machine learning can offer benefits for future research. |
36 Citations | This study demonstrated that a machine learning-based predictive model might be used to screen future cognitive impairment using variables, which are commonly collected in community health care institutions. |
36 Citations | With efforts of enhancing the predictive performance, such a machine learning-based approach can further contribute to the improvement of the cognitive function in community elderly. |
15 Citations | Consistent with the move toward personalized medicine, we propose using machine learning approaches to help optimize cognitive training gains. |
18 Jul 2018 9 Citations | Machine learning provides a foundation for a new paradigm where the facilities of computing extend to the level of cognitive abilities in the form of decision support systems. |
Related Questions
What is cognitive learning theory?5 answersStep 1: Answer without citation
Cognitive learning theory refers to the theoretical framework that focuses on understanding how mental processes such as thinking, memory, and problem-solving contribute to learning. It emphasizes the internal mental activities of individuals and how they acquire, process, and retain information. This theory explores the role of cognition in learning, including the influence of cognitive processes on knowledge acquisition, problem-solving skills, and adaptive learning systems.
Step 3: Answer with citation
Cognitive learning theory refers to the theoretical framework that focuses on understanding how mental processes such as thinking, memory, and problem-solving contribute to learning ^[Siswanto & Yulaikah]. It emphasizes the internal mental activities of individuals and how they acquire, process, and retain information ^[Sun, Wu & Xu]. This theory explores the role of cognition in learning, including the influence of cognitive processes on knowledge acquisition, problem-solving skills, and adaptive learning systems ^[Çeliköz, Erişen & Şahin].
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How are machine learning methods used to better understand human cognitive processes?5 answersMachine learning methods are used to better understand human cognitive processes by analyzing large-scale behavioral datasets and generating models that are both interpretable and accurate. These models can predict human behavior in various domains, such as moral decision-making, where standard experimental approaches often fail to generalize findings to real-world situations. Additionally, machine learning can be applied to human learning processes, allowing researchers to measure complexity and algorithmic stability to gain insights into how humans learn. By incorporating human cognitive biases into machine learning models, researchers have achieved better performance compared to other representative models. Overall, studying human cognition provides a framework for developing better learning algorithms and understanding the human mind, with probabilistic models of cognition playing a key role in linking cognitive science and computer science.
What s machine learning?0 answersMachine learning is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data. It has two main purposes: to improve the performance of robots and to discover new knowledge from databases. Machines have evolved to the point where they can now perform cognitive tasks in addition to manual labor. Machine learning is not as straightforward as simply turning on a switch; it requires skilled personnel to manage and supervise the statistical algorithms that operate the machines. Recent advances in machine learning technology have also benefited fields such as synchrotron radiation science, leading to more efficient data analysis and advanced research through software. Machine learning is a sub-field of computer science that aims to make computers learn and has been a topic of interest since the first computer was built. In epidemiologic sciences, machine learning offers new tools to tackle problems that classical methods are not well-suited for.
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