Artificial neural networks as clinical decision support systems

Abstract

Summary In the last decade, artificial intelligent systems based on neural networks have gradually become primary source for clinical decision support systems (CDSS) and are being used in diverse areas of medical diagnosis, classification, and prediction. An artificial neural network (ANN) consists of a large number of processing units which performs the computation in a parallel and distributed environment. They learn the pattern from the examples provided to it and then generalize based on the concepts they have learned while training. This paper presents a review of the current status of ANN and its variants as CDSS in various medical disciplines. The work focuses and describes the methods making use of simple ANN and use of real‐time approaches based on big data using ANN in cloud computing environment for various medical applications. Critical analysis of various methods based on smart approaches indicates that feed‐forward back propagation ANN performs sufficiently better in the domain of medicines with a high degree of accuracy.

Service Quality and Related Factors in Primary Health Care Services: A Cross-Sectional Study

“…According to studies, young, highly educated, and high-income individuals perceive lower levels of service quality [59]. Conversely, elderly, low-educated, and low-income individuals have lower expectations of health services but perceive service quality at a higher level [20,22]. In our study, educational level, marital status, and gender were found to be related to perceived service quality.…”

“…A number of studies conducted within the scope of health services have demonstrated that digital health technologies and artificial intelligence applications are playing an increasingly important role in the delivery of health services [19]. These technologies facilitate the provision of innovative and continuous healthcare services by enhancing the practicality of qualified and accurate patient management, expeditious and high-quality service delivery, and effective communication [20][21][22]. From the perspective of citizens, the utilization of digital health technologies and artificial intelligence applications has the potential to enhance satisfaction with health services.…”

Künstliche Intelligenz in der Medizin: Von Entlastungen und neuen Anforderungen im ärztlichen Handeln

“…Dies lässt sich prominent an zwei Beispielen aufzeigen, die teilweise bereits in klinischen Kontexten Anwendung finden: an KI-Systemen zur Bilderkennung und -segmentierung sowie an KI-Entscheidungsunterstützungssystemen (Shafi et al 2021). Die Anwendungsfelder für bilderkennende KI-Systeme sind außerordentlich vielfältig.…”

“Nothing works without the doctor:” Physicians’ perception of clinical decision-making and artificial intelligence

“…In the field of medicine, Artificial Intelligence–driven Decision Support Systems (AI-DSS) are currently receiving much attention. These AI applications based on machine learning or deep learning methods offer great potential to support clinical decision-making ( 2 , 3 ), for example by reducing the workload of medical staff ( 4 ).…”