Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Lubbock High School, Lubbock, TX 79401, USA.
Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Frenship High School, Lubbock, TX 79382, USA.
Ageing Res Rev. 2024 Aug;99:102410. doi: 10.1016/j.arr.2024.102410. Epub 2024 Jul 5.
Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting men and women at an exponentially growing rate, with currently no cure. Disease progression starts when dopaminergic neurons begin to die. In PD, the loss of neurotransmitter, dopamine is responsible for the overall communication of neural cells throughout the body. Clinical symptoms of PD are slowness of movement, involuntary muscular contractions, speech & writing changes, lessened automatic movement, and chronic tremors in the body. PD occurs in both familial and sporadic forms and modifiable and non-modifiable risk factors and socioeconomic conditions cause PD. Early detectable diagnostics and treatments have been developed in the last several decades. However, we still do not have precise early detectable biomarkers and therapeutic agents/drugs that prevent and/or delay the disease process. Recently, artificial intelligence (AI) science and machine learning tools have been promising in identifying early detectable markers with a greater rate of accuracy compared to past forms of treatment and diagnostic processes. Artificial intelligence refers to the intelligence exhibited by machines or software, distinct from the intelligence observed in humans that is based on neural networks in a form and can be used to diagnose the longevity and disease severity of disease. The term Machine Learning or Neural Networks is a blanket term used to identify an emerging technology that is created to work in the way of a "human brain" using many intertwined neurons to achieve the same level of raw intelligence as that of a brain. These processes have been used for neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease, to assess the severity of the patient's condition. In the current article, we discuss the prevalence and incidence of PD, and currently available diagnostic biomarkers and therapeutic strategies. We also highlighted currently available artificial intelligence science and machine learning tools and their applications to detect disease and develop therapeutic interventions.
帕金森病（PD）是全球第二常见的神经退行性疾病，其发病率呈指数级增长，目前尚无治愈方法。当多巴胺能神经元开始死亡时，疾病就开始进展。在 PD 中，神经递质多巴胺的丧失负责全身神经细胞的整体通讯。PD 的临床症状包括运动缓慢、不自主肌肉收缩、言语和书写变化、自动运动减少以及身体慢性震颤。PD 有家族性和散发性两种形式，可改变和不可改变的风险因素以及社会经济状况都会导致 PD。在过去几十年中，已经开发出了早期可检测的诊断和治疗方法。然而，我们仍然没有精确的早期可检测生物标志物和治疗剂/药物来预防和/或延缓疾病进程。最近，人工智能（AI）科学和机器学习工具在识别早期可检测标志物方面表现出了很高的准确性，这比过去的治疗和诊断过程要好。人工智能是指机器或软件表现出的智能，与人类观察到的基于神经网络的智能不同，它可以用于诊断疾病的寿命和疾病严重程度。术语“机器学习”或“神经网络”是一个通用术语，用于识别一种新兴技术，该技术旨在以类似于“人脑”的方式工作，使用许多相互交织的神经元来达到与大脑相同的原始智能水平。这些过程已被用于帕金森病和阿尔茨海默病等神经退行性疾病，以评估患者病情的严重程度。在本文中，我们讨论了 PD 的流行率和发病率，以及目前可用的诊断生物标志物和治疗策略。我们还强调了目前可用的人工智能科学和机器学习工具及其在检测疾病和开发治疗干预措施方面的应用。
