Currently, 47 million people live with dementia globally, and it is estimated to increase more than threefold (~131 million) by 2050. Alzheimer's disease (AD) is one of the major causative factors to induce progressive dementia. AD is a neurodegenerative disease, and its pathogenesis has been attributed to extracellular aggregates of amyloid β (Aβ) plaques and intracellular neurofibrillary tangles made of hyperphosphorylated τ-protein in cortical and limbic areas of the human brain. It is characterized by memory loss and progressive neurocognitive dysfunction. The anomalous processing of APP by β-secretases and γ-secretases leads to production of Aβ40 and Aβ42 monomers, which further oligomerize and aggregate into senile plaques. The disease also intensifies through infectious agents like HIV. Additionally, during disease pathogenesis, the presence of high concentrations of Aβ peptides in central nervous system initiates microglial infiltration. Upon coming into vicinity of Aβ, microglia get activated, endocytose Aβ, and contribute toward their clearance via TREM2 surface receptors, simultaneously triggering innate immunoresponse against the aggregation. In addition to a detailed report on causative factors leading to AD, the present review also discusses the current state of the art in AD therapeutics and diagnostics, including labeling and imaging techniques employed as contrast agents for better visualization and sensing of the plaques. The review also points to an urgent need for nanotechnology as an efficient therapeutic strategy to increase the bioavailability of drugs in the central nervous system.

Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, cancer diagnosis, and diabetes management. The role of AI in supporting advanced robotic surgeries developed for advanced biomedical applications is also discussed in this article. The position and importance of AI in improving the functionality, detection accuracy, decision-making ability of IoMT devices, and evaluation of associated risks assessment is discussed carefully and critically in this review. This review also encompasses the technological and engineering challenges and prospects for AI-based cloud-integrated personalized IoMT devices for designing efficient POC biomedical systems suitable for next-generation intelligent healthcare.