When it comes to Parkinson's disease, one of the most important issues revolves around early detection and accurate diagnosis. The intricacies of this neurodegenerative disorder often elude timely identification, leaving patients and healthcare providers grappling with its progressive symptoms. Ethical concerns surrounding the use of machine learning to aid in diagnosis further complicate this challenge. This issue is particularly significant for research scholars, PhD fellows, post-doc fellows, and medical and biomedical scholars seeking to unravel the mysteries of Parkinson's disease and develop more effective treatments. Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis serves as a beacon of hope in the quest to revolutionize Parkinson's disease diagnosis and treatment. It unveils the remarkable potential of artificial intelligence (AI) and machine learning (ML) in remodeling the way we approach this debilitating condition. With a comprehensive exploration of AI's capacity to analyze speech patterns, brain imaging data, and gait patterns, this book offers a powerful solution to the challenges of early detection and accurate diagnosis.

Parkinson's disease is diagnosed by history and physical examination and there are no laboratory investigations available to aid the diagnosis of Parkinson's disease. Confirmation of diagnosis of Parkinson's disease thus remains a difficulty. This book brings forth an update of most recent developments made in terms of biomarkers and various imaging techniques with potential use for diagnosing Parkinson's disease. A detailed discussion about the differential diagnosis of Parkinson's disease also follows as Parkinson's disease may be difficult to differentiate from other mimicking conditions at times. As Parkinson's disease affects many systems of human body, a multimodality treatment of this condition is necessary to improve the quality of life of patients. This book provides detailed information on the currently available variety of treatments for Parkinson's disease including pharmacotherapy, physical therapy and surgical treatments of Parkinson's disease. Postoperative care of patients of Parkinson's disease has also been discussed in an organized manner in this text. Clinicians dealing with day to day problems caused by Parkinson's disease as well as other healthcare workers can use beneficial treatment outlines provided in this book.

Stemming from environmental, genetic, and situational factors, chronic disease is a critical concern in modern medicine. Managing treatment and controlling symptoms is imperative to the longevity and quality of life of patients with such diseases. The Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions features current research on the diagnosis, monitoring, management, and treatment of recurring diseases such as diabetes, Parkinson's disease, autoimmune disorders, and others. This handbook is intended for practitioners and researchers across various disciplines including, but not limited to, biology, biomedical engineering, computer science, and information and communication technologies. Aimed at identifying new disease determinants and the way in which new technologies can contribute to improved health outcomes, this handbook covers a variety of topics, including wearable and mobile technologies, capillaroscopy imaging, diagnostic and monitoring methods, and disease prediction modeling, among others.

On March 3-4, 2016, the National Academies of Sciences, Engineering, and Medicine's Forum on Neuroscience and Nervous System Disorders held a workshop in Washington, DC, bringing together key stakeholders to discuss opportunities for improving the integrity, efficiency, and validity of clinical trials for nervous system disorders. Participants in the workshop represented a range of diverse perspectives, including individuals not normally associated with traditional clinical trials. The purpose of this workshop was to generate discussion about not only what is feasible now, but what may be possible with the implementation of cutting-edge technologies in the future.