AI-powered blockchain technology for public health: A contemporary review, open challenges, and future research directions
Blockchain technology has been growing at a substantial growth rate over the last decade.
Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application …
Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application …
A review on Alzheimer's disease classification from normal controls and mild cognitive impairment using structural MR images
Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder that degrades
the memory and cognitive ability in elderly people. The main reason for memory loss and …
the memory and cognitive ability in elderly people. The main reason for memory loss and …
A representation coefficient-based k-nearest centroid neighbor classifier
A novel deep learning approach for accurate cancer type and subtype identification
Cancer is a disease where abnormal cells grow uncontrollably and spread to other body
parts. It can originate anywhere in the human body, which consists of trillions of cells. These …
parts. It can originate anywhere in the human body, which consists of trillions of cells. These …
Advances in exosome plasmonic sensing: Device integration strategies and AI-aided diagnosis
X Lin, J Zhu, J Shen, Y Zhang, J Zhu - Biosensors and Bioelectronics, 2024 - Elsevier
Exosomes, as next-generation biomarkers, has great potential in tracking cancer
progression. They face many detection limitations in cancer diagnosis. Plasmonic …
progression. They face many detection limitations in cancer diagnosis. Plasmonic …
Evaluating the feasibility of machine learning algorithms for combustion regime classification in biodiesel-fueled homogeneous charge compression ignition engines
The present study explores the feasibility of machine-learning algorithms in classifying the
combustion regimes in a homogenous charge compression ignition (HCCI) engine fueled …
combustion regimes in a homogenous charge compression ignition (HCCI) engine fueled …
Classification framework for healthy hairs and alopecia areata: a machine learning (ml) approach
Alopecia areata is defined as an autoimmune disorder that results in hair loss. The latest
worldwide statistics have exhibited that alopecia areata has a prevalence of 1 in 1000 and …
worldwide statistics have exhibited that alopecia areata has a prevalence of 1 in 1000 and …
Contrastive learning for fair graph representations via counterfactual graph augmentation
Graph neural networks (GNNs) have exhibited excellent performance in graph
representation learning. However, GNNs might inherit biases from the data, leading to …
representation learning. However, GNNs might inherit biases from the data, leading to …