Ethical Considerations and Challenges in Neurodegenerative Diseases Using Machine Learning

Ethical Considerations and Challenges in Neurodegenerative Diseases Using Machine Learning

Moushumi Das, Hitakshi Hitakshi, Vandana Mohindru Sood, Kamal Deep Garg, Sushil Kumar Narang
DOI: 10.4018/979-8-3693-1281-0.ch011
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Abstract

Neurodegenerative illnesses, some of the most common diseases affecting public health, are affecting an increasing number of nations on a daily basis. Alzheimer's disease (AD) and other neurodegenerative disorders, such as Parkinson's disease (PD) and Huntington's disease (HD), cause gradual declines in cognitive, motor, emotional, and functional abilities and have a significant impact on activities of daily life (ADL) and quality of life. Because of major improvements in digital technology over the last 10 years, digital endpoints may now be integrated into clinical trials to change how neurodegenerative symptoms are diagnosed and tracked. A few additional challenges must be considered to protect those interests. In this chapter, the moral and legal difficulties surrounding the use of technology-assisted treatment for neurodegenerative disorders will be discussed along with a new technique using machine learning algorithms that would work upon the prevailing challenges and come out with better results.
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Introduction

Neurodegenerative disorders are a group of ailments that cause the nervous system, particularly the neurons in the brain and spinal cord, to degrade progressively and irreversibly. As the disease advances, symptoms such as cognitive decline, motor dysfunction, and sensory abnormalities frequently worsen. Many illnesses are distinguished by the accumulation of misfolded or aggregated proteins, which disrupt normal cellular activities and result in cell death (Mamun et al. 2022). As a result of this neuronal loss, cognitive, motor, and sensory functions gradually decrease, which differs depending on the situation. Neurodegenerative diseases provide significant diagnostic and therapeutic challenges due to their complex underlying mechanisms and lack of effective treatments. (Shusharina et al. 2023).

Alzheimer's disease is fundamentally characterised by the buildup of aberrant protein aggregates in the brain. Beta-amyloid plaques, which are made of beta-amyloid protein that has been improperly folded, collect outside neurons, whereas tau tangles create twisted formations inside these vital brain cells. These protein anomalies impair normal neuronal transmission and function, which ultimately causes neurons to die (Zhao et al. 2020). It generally goes unnoticed in its early stages, and typically begins with moderate cognitive impairment and subtle memory difficulties. As the disease progresses in patients, a wide range of cognitive impairments, including as confusion, disorientation, language issues, and reduced problem-solving skills, worsen. Alzheimer's disease takes a heavy toll in its latter stages, causing severe memory loss, inability to recognise loved ones, and a decline in basic self-care abilities. Alzheimer's disease is distressing in its progression, emphasising the vital need for additional research into its causes, prevention, and treatment (Marx et al. 2020).

Parkinson's disease is a neurological disorder that mostly inhibits movement control and worsens over time. It exhibits both motor and non-motor symptoms. Parkinson's disease is fundamentally defined by the loss of dopamine-producing neurons in the brain's substantia nigra. As a result of this neuronal loss, dopamine, a neurotransmitter important for regulating smooth and coordinated movement, is inadequate. The disease's three chief motor symptoms are tremors (involuntary shaking, especially at rest), bradykinesia (slowness of movement that interferes with daily activities), and rigidity (muscle stiffness and unwillingness to move). Falls are more likely as a result of the gait irregularities and postural instability caused by certain motor impairments (Jin et al. 2023). Parkinson's disease is a complex disease that continues to have an impact on the lives of those who suffer from it, driving further research into its causes and potential treatments (Olaniyan et al. 2023).

Huntington's sickness (HD) is an innate and perseveringly moderate neurodegenerative problem that significantly influences development, insight, and conduct. This staggering illness emerges from a change in the HTT quality, prompting the development of a poisonous protein called huntingtin. As the transformed huntingtin collects in the cerebrum, it sets off the steady degeneration of neurons, especially in the basal ganglia and cortex. The most prominent early side effect is compulsory and jerky developments known as chorea, yet as HD propels, people experience a wide exhibit of debilitations (Mohammed et al. 2019).

These incorporate mental deterioration, with troubles in memory and direction, as well as mental side effects like wretchedness, uneasiness, and character changes. HD presents a huge test for impacted people and their families, as it determinedly dissolves both physical and mental capacities. As of now, there is no remedy for Huntington's sickness, however side effect the executives and backing from medical services experts and parental figures assume an essential part in upgrading the personal satisfaction for those living with this difficult condition. Examination into possible medicines and treatments is progressing, offering expect what's in store (Hoffmann et al. 2020).

Key Terms in this Chapter

Parkinson’s Disease: Parkinson's disease is a neurodegenerative disorder affecting movement, causing tremors, stiffness, and impaired balance, primarily due to the loss of dopamine-producing neurons in the brain's substantia nigra region.

Machine Learning: Machine learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, using algorithms to recognize patterns and make predictions.

Deep Learning: Deep learning is a subset of machine learning where artificial neural networks with multiple layers (deep neural networks) learn intricate patterns from large datasets, allowing for complex tasks such as image and speech recognition.

Convolutional Neural Networks: Convolutional neural networks (CNNs) are deep learning models specifically designed for processing grid-like data, using convolutional layers to automatically and adaptively learn spatial hierarchies of features from input images.

Huntington's Disease: Huntington's disease is a hereditary neurodegenerative disorder causing motor dysfunction, cognitive decline, and psychiatric symptoms due to abnormal repeats of the HTT gene.

Neurodegenerative Disorders: Neurodegenerative disorders are a group of diseases characterized by the progressive degeneration of the structure and function of the nervous system.

Reverberation Imaging: Reverberation imaging refers to medical imaging techniques that utilize sound waves (ultrasound) to create detailed images of internal structures, particularly useful in visualizing organs and tissues.

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