ABSTRACT
The cognitive impairment known as dementia affects millions of individuals throughout the globe. The use of machine learning (ML) and deep learning (DL) algorithms has shown great promise as a means of early identification and treatment of dementia. Dementias such as Alzheimer's Dementia, frontotemporal dementia, Lewy body dementia, and vascular dementia are all discussed in this article, along with a literature review on using ML algorithms in their diagnosis. Different ML algorithms, such as support vector machines, artificial neural networks, decision trees, and random forests, are compared and contrasted, along with their benefits and drawbacks. As discussed in this article, accurate ML models may be achieved by carefully considering feature selection and data preparation. We also discuss how ML algorithms can predict disease progression and patient responses to therapy. However, overreliance on ML and DL technologies should be avoided without further proof. It's important to note that these technologies are meant to assist in diagnosis but should not be used as the sole criteria for a final diagnosis. The research implies that ML algorithms may help increase the precision with which dementia is diagnosed, especially in its early stages. The efficacy of ML and DL algorithms in clinical contexts must be verified, and ethical issues around the use of personal data must be addressed, but this requires more study.
ABSTRACT
Aging significantly impacts several age-related neurological problems, such as stroke, brain tumors, oxidative stress, neurodegenerative diseases (Alzheimer's, Parkinson's, and dementia), neuroinflammation, and neurotoxicity. Current treatments for these conditions often come with side effects like hallucinations, dyskinesia, nausea, diarrhea, and gastrointestinal distress. Given the widespread availability and cultural acceptance of natural remedies, research is exploring the potential effectiveness of plants in common medicines. The ancient medical system used many botanical drugs and medicinal plants to treat a wide range of diseases, including age-related neurological problems. According to current clinical investigations, berries improve motor and cognitive functions and protect against age-related neurodegenerative diseases. Additionally, berries may influence signaling pathways critical to neurotransmission, cell survival, inflammation regulation, and neuroplasticity. The abundance of phytochemicals in berries is believed to contribute to these potentially neuroprotective effects. This review aimed to explore the potential benefits of berries as a source of natural neuroprotective agents for age-related neurological disorders.