CEREBRAL PALSY: BRIDGING CLINICAL PRACTICE AND RESEARCH ADVANCES

Abstract

Permanent movement deficits as an outcome of non-progressive disruptions during the process of cerebral development are the hallmark of cerebral palsy (CP), a common-developmental condition. Greater immaturity and lower birth weight are associated with a higher prevalence of CP. CP continues to be a leading cause of childhood disability globally, despite improvements in clinical care. The gap between discovery and application can be closed by combining state-of-the-art research with patient-centered clinical practice, offering new hope for improving the quality of life of individuals with cerebral palsy and their families. Recent advancements also demonstrate how Artificial intelligence (AI) has the potential to revolutionize CP  management.-powered technologies are improving early diagnosis by using predictive modeling and sophisticated image analysis. Early treatments are made possible by machine learning algorithms that assist in detecting infants who are at risk even before clinical symptoms manifest. Children with cerebral palsy are benefitting from improved movement, communication, and rehabilitation results thanks to robotics and AI-based assistive technologies. The continuous attempts to connect clinical practice with new research are highlighted in this study. It discusses on early diagnosis, management techniques meant to improve patient outcomes, and the growing understanding of CP risk factors. The way that care is provided is changing as a result of recent scientific developments in fields including Neuron-protective medicines, regenerative medicine, and rehabilitation technology. Furthermore, more effective and customized treatment techniques are being made possible by AI applications in remote patient monitoring and individualized therapy planning.