[HTML][HTML] A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities
Administrative and medical processes of the healthcare organizations are rapidly changing
because of the use of artificial intelligence (AI) systems. This change demonstrates the …
because of the use of artificial intelligence (AI) systems. This change demonstrates the …
[HTML][HTML] Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review
Objectives Patient representation learning refers to learning a dense mathematical
representation of a patient that encodes meaningful information from Electronic Health …
representation of a patient that encodes meaningful information from Electronic Health …
Analysis of healthcare big data
Z Lv, L Qiao - Future Generation Computer Systems, 2020 - Elsevier
In order to explore the development of healthcare in China and the privacy and security risk
factors in medical data under the background of big data, the development status of China's …
factors in medical data under the background of big data, the development status of China's …
[HTML][HTML] Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Objective Temporal electronic health records (EHRs) contain a wealth of information for
secondary uses, such as clinical events prediction and chronic disease management …
secondary uses, such as clinical events prediction and chronic disease management …
Predicting hospital readmission via cost-sensitive deep learning
With increased use of electronic medical records (EMRs), data mining on medical data has
great potential to improve the quality of hospital treatment and increase the survival rate of …
great potential to improve the quality of hospital treatment and increase the survival rate of …
Machine learning in the prediction of medical inpatient length of stay
Length of stay (LOS) estimates are important for patients, doctors and hospital
administrators. However, making accurate estimates of LOS can be difficult for medical …
administrators. However, making accurate estimates of LOS can be difficult for medical …
[HTML][HTML] SECNLP: A survey of embeddings in clinical natural language processing
Distributed vector representations or embeddings map variable length text to dense fixed
length vectors as well as capture prior knowledge which can transferred to downstream …
length vectors as well as capture prior knowledge which can transferred to downstream …
Providing healthcare-as-a-service using fuzzy rule based big data analytics in cloud computing
With advancements in information and communication technology, there is a steep increase
in the remote healthcare applications in which patients can get treatment from the remote …
in the remote healthcare applications in which patients can get treatment from the remote …
Appositeness of optimized and reliable machine learning for healthcare: a survey
Abstract Machine Learning (ML) has been categorized as a branch of Artificial Intelligence
(AI) under the Computer Science domain wherein programmable machines imitate human …
(AI) under the Computer Science domain wherein programmable machines imitate human …
Edge server deployment for health monitoring with reinforcement learning in internet of medical things
The Internet of Medical Things (IoMT) has recently gained a lot of interest in the health care
industry. IoMT enables real-time and omnipresent monitoring of a patient's health status …
industry. IoMT enables real-time and omnipresent monitoring of a patient's health status …