Deep Learning in Healthcare System for Quality of Service.
Dibyahash BordoloiVijay SinghSumaya SanoberSeyed Mohammed BuhariJaved Ahmed UjjanRajasekhar BodduPublished in: Journal of healthcare engineering (2022)
Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the healthcare systems. In the present healthcare system, the implementation of ML and DL is extensive to achieve a higher quality of service and quality of health to patients, doctors, and healthcare professionals. ML and DL were found to be effective in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This work presents a state-of-the-art review on the recent advancements in ML and DL and their implementation in the healthcare systems for achieving multi-objective goals. A total of 10 papers have been thoroughly reviewed that presented novel works of ML and DL integration in the healthcare system for achieving various targets. This will help to create reference data that can be useful for future implementation of ML and DL in other sectors of healthcare system.
Keyphrases
- healthcare
- deep learning
- machine learning
- quality improvement
- mental health
- drug delivery
- drug discovery
- primary care
- big data
- artificial intelligence
- public health
- endothelial cells
- health information
- convolutional neural network
- randomized controlled trial
- ejection fraction
- newly diagnosed
- liver failure
- climate change
- risk assessment
- induced pluripotent stem cells
- real time pcr
- human health
- loop mediated isothermal amplification
- drug induced
- extracorporeal membrane oxygenation
- social media
- label free