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Neurosciences

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Claude, ChatGPT, Copilot, and Gemini performance versus students in different topics of neuroscience.

Advances in physiology education
Despite extensive studies on large language models and their capability to respond to questions from various licensed exams, there has been limited focus on employing chatbots for specific subjects within the medical curriculum, specifically medical ...

Neurocyberethics, a new and pertinent approach to neuroethics.

Gaceta medica de Mexico
Ethics in neuroscience presents an evolutionary development that has required a more punctual attention, from the knowledge of functional neuroimaging that defines the structures related to the emotions and cognitive functions. Systematic review in P...

Knowledge mining of brain connectivity in massive literature based on transfer learning.

Bioinformatics (Oxford, England)
MOTIVATION: Neuroscientists have long endeavored to map brain connectivity, yet the intricate nature of brain networks often leads them to concentrate on specific regions, hindering efforts to unveil a comprehensive connectivity map. Recent advanceme...

Low-Cost Approaches in Neuroscience to Teach Machine Learning Using a Cockroach Model.

eNeuro
In an effort to increase access to neuroscience education in underserved communities, we created an educational program that utilizes a simple task to measure place preference of the cockroach () and the open-source free software, SLEAP Estimates Ani...

Neuroevolution insights into biological neural computation.

Science (New York, N.Y.)
This article reviews existing work and future opportunities in neuroevolution, an area of machine learning in which evolutionary optimization methods such as genetic algorithms are used to construct neural networks to achieve desired behavior. The ar...

Integrating neuroscience and artificial intelligence: EEG analysis using ensemble learning for diagnosis Alzheimer's disease and frontotemporal dementia.

Journal of neuroscience methods
BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are both progressive neurological disorders that affect the elderly. Distinguishing between individuals suffering from these two diseases in the early stages can be quite challeng...

Task relevant autoencoding enhances machine learning for human neuroscience.

Scientific reports
In human neuroscience, machine learning can help reveal lower-dimensional neural representations relevant to subjects' behavior. However, state-of-the-art models typically require large datasets to train, and so are prone to overfitting on human neur...

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

Sensors (Basel, Switzerland)
This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. Additionally, the stimuli used in the stu...

Letters to the editor generated by AI in neuroscience: The role of neuroethics.

Neuroscience
The letter to the editor (LTE) is a correspondence forum that allows a journal's readers to comment on published research and also publish data and arguments in a brief way. The LTE has vital functions as an accessible comment forum, including holdin...

Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

Journal of healthcare management / American College of Healthcare Executives
GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary care center and safety net hospital with more than 50,000 discharges and 30,000 surgical procedures per year. TGH collaborated with GE HealthCare Comm...