Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...
Electroencephalography (EEG) is a fascinating noninvasive technique that measures and records the brain's electrical activity. It detects small electrical signals produced when neurons in the brain ...
Spatially and temporally overlapping target and distractor are both rhythmically sampled at ~1 Hz, and the phase relationship between target sampling and distractor sampling predicts behavior.
Ultrafiltration membranes used in pharmaceutical manufacturing and other industrial processes have long relied on separating ...
Yoshua Bengio talks about his efforts to identify — and address — the risks posed by AI.
Deep Learning with Yacine on MSN
Sleep Stage Classification with Python: EEG, Scikit-Learn & MNE
Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like ...
Researchers successfully developed a machine learning-based method for predicting symptom deterioration in patients with cancer.
Recently, a research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a ...
The rapid development and integration of artificial intelligence (AI), including predictive, generative, and emerging agentic ...
We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback