[HTML][HTML] Deep Learning applications for COVID-19
This survey explores how Deep Learning has battled the COVID-19 pandemic and provides
directions for future research on COVID-19. We cover Deep Learning applications in Natural …
directions for future research on COVID-19. We cover Deep Learning applications in Natural …
Large language models in health care: Development, applications, and challenges
R Yang, TF Tan, W Lu, AJ Thirunavukarasu… - Health Care …, 2023 - Wiley Online Library
Recently, the emergence of ChatGPT, an artificial intelligence chatbot developed by OpenAI,
has attracted significant attention due to its exceptional language comprehension and …
has attracted significant attention due to its exceptional language comprehension and …
Machine learning for clinical decision support in infectious diseases: a narrative review of current applications
Background Machine learning (ML) is a growing field in medicine. This narrative review
describes the current body of literature on ML for clinical decision support in infectious …
describes the current body of literature on ML for clinical decision support in infectious …
Data mining in clinical big data: the frequently used databases, steps, and methodological models
WT Wu, YJ Li, AZ Feng, L Li, T Huang, AD Xu… - Military Medical …, 2021 - Springer
Many high quality studies have emerged from public databases, such as Surveillance,
Epidemiology, and End Results (SEER), National Health and Nutrition Examination Survey …
Epidemiology, and End Results (SEER), National Health and Nutrition Examination Survey …
An attention based deep learning model of clinical events in the intensive care unit
This study trained long short-term memory (LSTM) recurrent neural networks (RNNs)
incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and …
incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and …
Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory
Background Unplanned readmission of a hospitalized patient is an indicator of patients'
exposure to risk and an avoidable waste of medical resources. In addition to hospital …
exposure to risk and an avoidable waste of medical resources. In addition to hospital …
Transfer learning for non-image data in clinical research: a scoping review
A Ebbehoj, MØ Thunbo, OE Andersen… - PLOS Digital …, 2022 - journals.plos.org
Background Transfer learning is a form of machine learning where a pre-trained model
trained on a specific task is reused as a starting point and tailored to another task in a …
trained on a specific task is reused as a starting point and tailored to another task in a …
Triglyceride-glucose index linked to all-cause mortality in critically ill patients: a cohort of 3026 patients
Y Liao, R Zhang, S Shi, Y Zhao, Y He, L Liao… - Cardiovascular …, 2022 - Springer
Abstract Background Triglyceride-glucose (TyG) index as a reliable surrogate of insulin
resistance (IR) has been shown to be related to adverse clinical outcomes in patients with …
resistance (IR) has been shown to be related to adverse clinical outcomes in patients with …
Artificial intelligence and deep learning in ophthalmology
Artificial intelligence (AI), in particular deep learning (DL), has gained significant interest
recently from healthcare systems. DL has been widely applied to detect and classify major …
recently from healthcare systems. DL has been widely applied to detect and classify major …
[HTML][HTML] Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies
Background Machine learning (ML) is increasingly being used in many areas of health care.
Its use in infection management is catching up as identified in a recent review in this journal …
Its use in infection management is catching up as identified in a recent review in this journal …