Scalable healthcare assessment for diabetic patients using deep learning on multiple GPUs

D Sierra-Sosa, B Garcia-Zapirain… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The large-scale parallel computation that became available on the new generation of
graphics processing units (GPUs) and on cloud-based services can be exploited for use in …

The risk to population health equity posed by automated decision systems: A narrative review

M Burger - arXiv preprint arXiv:2001.06615, 2020 - arxiv.org
Artificial intelligence is already ubiquitous, and is increasingly being used to autonomously
make ever more consequential decisions. However, there has been relatively little research …

Deep Learning-Based analytic framework using comprehensive urbanization index for heat vulnerability assessment in urban areas

Y Kim, Y Kim - Expert Systems with Applications, 2024 - Elsevier
The objective of this study was to propose an analytic framework for heat vulnerability based
on the detailed spatial unit of a city. Data were analyzed for Daegu city, South Korea, during …

A contemporary review on soft computing techniques for thyroid identification and detection

R Srivastava, P Kumar - International Journal of Computer …, 2022 - inderscienceonline.com
This paper is aimed to review various soft computing techniques for identification and
detection of thyroid disorder. The papers are extracted from reputable databases like …

Advanced method for the Analyses of Large Amounts of Data using deep learning in Health Sector

V Gavekar, DP Lele, M Kumbhar - Journal of Algebraic Statistics, 2022 - publishoa.com
Large amounts of data, rising costs, and a focus on personalised care have all led to a rise
in the use of" big data" in healthcare over the past few years." Big data processing" is a term …