Deep Learning in Smart Health: Methodologies, Applications, Challenges

Artificial intelligence-based public healthcare systems: G2G knowledge-based exchange to enhance the decision-making process

“…Moreover, particular AI applications, such as chatbots, have helped to improve the efficiency and privacy of the process of receiving and addressing patients' inquiries (Nadarzynski et al, 2019;Vimalkumar et al, 2021). AI enjoys a wide range of practical features that make such systems much smarter and more efficient in comparison with human intelligence, especially in relation to visuospatial processing speed, pattern recognition, and prediction of disease, thereby enabling better diagnoses (Kummitha, 2020;Simsek et al, 2020;Wahl et al, 2018). Therefore, AI can perform critical healthcare tasks as well as or better than humans, such as the diagnosis of diseases using the AI-based COVID-19 problem-solving task (Davenport & Kalakota, 2019).…”

“…AI is superior in some respects to human intelligence, such as in visuospatial processing speed and pattern recognition, but it lags behind in terms of reasoning, new skill learning, and creativity (Wahl et al, 2018). Prediction of disease and improving an individual's healthcare can be made more efficient by integrating computing systems with AI methodologies (Simsek et al, 2020). AI-based healthcare technologies can imitate human intelligence by classifying and predicting patient diseases using specific predictive and analytical approaches (Raza, 2020).…”

Autoencoder Composite Scoring to Evaluate Prosthetic Performance in Individuals with Lower Limb Amputation

“…Multilayer neural networks in deep learning are capable of taking into account the complex nonlinear mathematical relationships among measures that challenged previous outcome modeling strategies [ 7 ]. In the biomedical field, deep learning methods increasingly perform a vital role in inference as part of smart healthcare systems [ 8 ]. Yang et al proposed a convolutional neural network and predicted an expanded disability status scale (EDSS) to measure the severity of multiple sclerosis [ 9 ].…”