Involvement of machine learning tools in healthcare decision making
SMDAC Jayatilake… - Journal of healthcare …, 2021 - Wiley Online Library
In the present day, there are many diseases which need to be identified at their early stages
to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason …
to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason …
The utility of language models in cardiology: a narrative review of the benefits and concerns of ChatGPT-4
D Gala, AN Makaryus - … Journal of Environmental Research and Public …, 2023 - mdpi.com
Artificial intelligence (AI) and language models such as ChatGPT-4 (Generative Pretrained
Transformer) have made tremendous advances recently and are rapidly transforming the …
Transformer) have made tremendous advances recently and are rapidly transforming the …
[HTML][HTML] Can ChatGPT provide intelligent diagnoses? A comparative study between predictive models and ChatGPT to define a new medical diagnostic bot
Intelligent diagnosis processes rely on Artificial Intelligence (AI) techniques to provide
possible diagnoses by analyzing patient data and medical information. To make accurate …
possible diagnoses by analyzing patient data and medical information. To make accurate …
A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future
RJ Woodman, AA Mangoni - Aging Clinical and Experimental Research, 2023 - Springer
The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …
research, including data-hungry deep learning algorithms. More computationally efficient …
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …
remarkable performance in providing medical professionals and patients with support for …
Cross-validation of predictive models for functional recovery after post-stroke rehabilitation
Background Rehabilitation treatments and services are essential for the recovery of post-
stroke patients' functions; however, the increasing number of available therapies and the …
stroke patients' functions; however, the increasing number of available therapies and the …
Delineation of the electrocardiogram with a mixed-quality-annotations dataset using convolutional neural networks
Detection and delineation are key steps for retrieving and structuring information of the
electrocardiogram (ECG), being thus crucial for numerous tasks in clinical practice. Digital …
electrocardiogram (ECG), being thus crucial for numerous tasks in clinical practice. Digital …
[HTML][HTML] Attri-VAE: Attribute-based interpretable representations of medical images with variational autoencoders
Deep learning (DL) methods where interpretability is intrinsically considered as part of the
model are required to better understand the relationship of clinical and imaging-based …
model are required to better understand the relationship of clinical and imaging-based …
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …
point of care applications; however, many challenges such as data privacy concerns impede …
A survey of generative adversarial networks for synthesizing structured electronic health records
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …
point of care applications; however, many challenges such as data privacy concerns impede …