Background This review aims to systematically evaluate the currently available evidence
investigating the use of artificial intelligence (AI) and machine learning (ML) in the field of …

Background As diagnostic and prognostic models developed by traditional statistics perform
poorly in real-world, artificial intelligence (AI) and Big Data (BD) may improve the supply …

The objective of the present study was to investigate whether deep learning could be
applied successfully to the classification of images from colposcopy. For this purpose, a total …

learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …

Background Kidney transplantation is the optimal treatment for patients with end-stage renal
disease. Short-and long-term kidney graft survival is influenced by a number of donor and …

Background: We explored whether the use of deep learning to model combinations of
symptom-physical signs and objective tests, such as lung function tests and the bronchial …

Background Recent advances in machine learning have given rise to deep learning, which
uses hierarchical layers to build models, offering the ability to advance value-based …

MicroRNA (miRNA) is a small non-coding molecule that is involved in gene regulation and
RNA silencing by complementary on their targets. Experimental methods for target …

Background: The use of AI-driven technologies in probing big data to generate better risk
prediction models has been an ongoing and expanding area of investigation. The AI-driven …

Background Machine learning (ML) is developing fast with promising prospects within
medicine and already has several applications in perioperative care. We conducted a …