About this Research Topic
The aim of this Research Topic is to gather and spotlight innovative applications of machine learning and other cutting-edge tools in predicting and treating stroke. We aim to provide a platform for researchers to share their advancements, thus accelerating the integration of these applications into clinical practice. We anticipate that the gathered works will generate a holistic understanding of the current landscape, identify gaps that still need to be addressed, and inspire the development of future technologies in stroke prediction and treatment.
This Research Topic aims to cover a wide spectrum of areas in machine learning and cutting-edge technology as applied to stroke prediction and treatment strategies. We invite manuscripts that focus on the following aspects:
-Design and development of machine learning algorithms specifically purposed for predicting stroke.
-Novel applications of artificial intelligence in different facets of stroke care, including but not limited to diagnosis, treatment, and follow-up processes.
-Integration and utilization of diverse data sources, from standard health records to novel biometric data from wearables in assessing stroke risk and administering personalized treatments.
-Studies evaluating the real-world clinical implications, effectiveness, and patient outcomes following the adoption of advanced technologies in stroke care settings.
-Exploration and utilization of publicly available datasets for the enhancement of stroke prediction systems.
-Investigations into ethical, legal, and social issues surrounding the use of these technologies in healthcare.
Please be aware that manuscripts dealing with stoke prediction and treatment, especially those that do not employ tools relevant to Computational Neuroscience, should accordingly be submitted to Frontiers in Stroke.
We welcome various manuscript types, highlighting original research, in-depth reviews, methodological advancements, and brief reports. All submissions should manifest innovation in stroke management, focusing on the role of machine learning and state-of-the-art technologies, and their potential or realized impact on clinical practice and patient outcomes.
Together, let's transform stroke prediction and treatment strategies for the future.
Keywords: Stroke Prediction, Machine Learning, Artificial Intelligence in Stroke Care, stroke
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.