Machine and deep learning algorithms for classifying different types of dementia: A literature review.

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.

Endoplasmic reticulum as a target in cardiovascular diseases: Is there a role for flavonoids?

Flavonoids are found in natural health products and plant-based foods. The flavonoid molecules contain a 15-carbon skeleton with the particular structural construction of subclasses. The most flavonoid's critical subclasses with improved health properties are the catechins or flavonols (e.g., epigallocatechin 3-gallate from green tea), the flavones (e.g., apigenin from celery), the flavanones (e.g., naringenin from citrus), the flavanols (e.g., quercetin glycosides from berries, onion, and apples), the isoflavones (e.g., genistein from soya beans) and the anthocyanins (e.g., cyanidin-3-O-glucoside from berries). Scientific data conclusively demonstrates that frequent intake of efficient amounts of dietary flavonoids decreases chronic inflammation and the chance of oxidative stress expressing the pathogenesis of human diseases like cardiovascular diseases (CVDs). The endoplasmic reticulum (ER) is a critical organelle that plays a role in protein folding, post-transcriptional conversion, and transportation, which plays a critical part in maintaining cell homeostasis. Various stimuli can lead to the creation of unfolded or misfolded proteins in the endoplasmic reticulum and then arise in endoplasmic reticulum stress. Constant endoplasmic reticulum stress triggers unfolded protein response (UPR), which ultimately causes apoptosis. Research has shown that endoplasmic reticulum stress plays a critical part in the pathogenesis of several cardiovascular diseases, including diabetic cardiomyopathy, ischemic heart disease, heart failure, aortic aneurysm, and hypertension. Endoplasmic reticulum stress could be one of the crucial points in treating multiple cardiovascular diseases. In this review, we summarized findings on flavonoids' effects on the endoplasmic reticulum and their role in the prevention and treatment of cardiovascular diseases.