Parkinson’s disease
Abstract (250)
The recent developments in data analysis and artificial intelligence have been increasingly employed in various fields to solve our day-to-day problems. These techniques have been employed in the field of medicine to ensure a high level of accuracy in the diagnosis of diseases. Parkinson’s disease (PD) is among the diseases that can be accurately diagnosed using these methods. PD is a neurodegenerative illness common among the elderly in the United States- it is more rampant in older men than in women. There are several symptoms of this disease that can be used for diagnosing this disease in the early stages. However, many people neglect the initial signs as a consequence of age.
Moreover, these symptoms are often mistaken with other diseases, thereby resulting in a delayed cure. This research uses finger movement characteristics for patients and compares them with control people, for instance, sidedness (left, right) and direction of the critical press. It also analyzes the duration of the hold time, the latency time, and variations in the press duration. Equally, it also uses tremors as a second cardinal symptom and length of disease to predict the change of features as the disease progresses over time. This research and data analysis aims to assist the community and the medical field in discovering symptoms of a silent epidemic in the early stages for easy detection and treatment.
Abstract 🙁 150 words)
Parkinson’s disease (PD) is a neurodegenerative illness common among the elderly in the United States. Data from the population on 36 million beneficiaries of Medicare over 65 years of age indicate that 1.6% of the American people are undertaking PD treatment yearly (cite this information). Many people neglect the early symptoms as a consequence of age—Cardinal symptoms of PD include shuffling gait and limb tremor, among others. This project’s main target is to use finger movement characteristics affected by Parkinson’s disease with ordinary people. It also analyzes the finger attributes of patients who take medication for PD and have other cardinal symptoms, such as tremors. The next part of this research is to develop predictive models that use this symptom to diagnose PD over time. The research work may have practical application in medical science and provide Doctors and other PD experts with new insights.