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[PDF][PDF] Large language models: a comprehensive survey of its applications, challenges, limitations, and future prospects
Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …
[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
Federated learning for smart healthcare: A survey
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …
Synthetic data generation for tabular health records: A systematic review
Synthetic data generation (SDG) research has been ongoing for some time with promising
results in different application domains, including healthcare, biometrics and energy …
results in different application domains, including healthcare, biometrics and energy …
An empirical survey of data augmentation for time series classification with neural networks
In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …
recognition. Part of this success can be attributed to the reliance on big data to increase …
Modeling tabular data using conditional gan
Modeling the probability distribution of rows in tabular data and generating realistic synthetic
data is a non-trivial task. Tabular data usually contains a mix of discrete and continuous …
data is a non-trivial task. Tabular data usually contains a mix of discrete and continuous …
Deep learning for time series classification
HI Fawaz - ar** deep learning models using electronic health records data: a systematic review
Objective To conduct a systematic review of deep learning models for electronic health
record (EHR) data, and illustrate various deep learning architectures for analyzing different …
record (EHR) data, and illustrate various deep learning architectures for analyzing different …
A multifaceted benchmarking of synthetic electronic health record generation models
Synthetic health data have the potential to mitigate privacy concerns in supporting
biomedical research and healthcare applications. Modern approaches for data generation …
biomedical research and healthcare applications. Modern approaches for data generation …