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Using Learning Outcome Measures to assess Doctoral Nursing Education10:07

Using Learning Outcome Measures to assess Doctoral Nursing Education

The structure and process for measuring student learning outcomes through customizable assessment rubrics is discussed and applied to a doctoral nursing education...
19.4K
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

The bottleneck for cellular 3D electron microscopy is feature extraction (segmentation) in highly complex 3D density maps. We have developed a set of criteria, which provides guidance regarding which segmentation approach (manual, semi-automated, or automated) is best suited for different data types, thus providing a starting point for effective...
25.0K
Bringing the Visible Universe into Focus with Robo-AO10:35

Bringing the Visible Universe into Focus with Robo-AO

Light from astronomical objects must travel through the earth's turbulent atmosphere before it can be imaged by ground-based telescopes. To enable direct imaging at maximum theoretical angular resolution, advanced techniques such as those employed by the Robo-AO adaptive-optics system must be...
20.1K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

This article describes RUGGED (Retrieval Under Graph-Guided Explainable disease Distinction), which integrates Large Language Model (LLM) inference with Retrieval-Augmented Generation (RAG). It draws evidence from expert-curated biomedical knowledge bases and peer-reviewed biomedical publications to synthesize new knowledge from up-to-date information, identify explainable and actionable predictions, and pinpoint promising directions for hypothesis-driven...
1.3K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Neuroimaging researchers typically consider the brain's response as the mean activity across repeated experimental trials and disregard signal variability over time as "noise". However, it is becoming clear that there is signal in that noise. This article describes the novel method of multiscale entropy for quantifying brain signal variability in the time...
34.4K
Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation06:32

Bringing the Clinic Home: An At-Home Multi-Modal Data Collection Ecosystem to Support Adaptive Deep Brain Stimulation

The protocol shows a prototype of the at-home multi-modal data collection platform that supports research optimizing adaptive deep brain stimulation (aDBS) for people with neurological movement disorders. We also present key findings from deploying the platform for over a year to the home of an individual with Parkinson's...
1.8K