Artificial intelligence applied to clinical trials: opportunities and challenges

S Askin, D Burkhalter, G Calado, S El Dakrouni - Health and technology, 2023 - Springer
Abstract Background Clinical Trials (CTs) remain the foundation of safe and effective drug
development. Given the evolving data-driven and personalized medicine approach in …

[HTML][HTML] Trends in using IoT with machine learning in health prediction system

A Aldahiri, B Alrashed, W Hussain - Forecasting, 2021 - mdpi.com
Machine learning (ML) is a powerful tool that delivers insights hidden in Internet of Things
(IoT) data. These hybrid technologies work smartly to improve the decision-making process …

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19

M Van der Schaar, AM Alaa, A Floto, A Gimson… - Machine Learning, 2021 - Springer
The COVID-19 global pandemic is a threat not only to the health of millions of individuals,
but also to the stability of infrastructure and economies around the world. The disease will …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

[HTML][HTML] Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products

Y Abdalla, M Elbadawi, M Ji, M Alkahtani… - International Journal of …, 2023 - Elsevier
Abstract Three-dimensional (3D) printing is drastically redefining medicine production,
offering digital precision and personalized design opportunities. One emerging 3D printing …

Estimating the effects of continuous-valued interventions using generative adversarial networks

I Bica, J Jordon… - Advances in Neural …, 2020 - proceedings.neurips.cc
While much attention has been given to the problem of estimating the effect of discrete
interventions from observational data, relatively little work has been done in the setting of …

Causal deep learning

J Berrevoets, K Kacprzyk, Z Qian… - arxiv preprint arxiv …, 2023 - arxiv.org
Causality has the potential to truly transform the way we solve a large number of real-world
problems. Yet, so far, its potential largely remains to be unlocked as causality often requires …

A review of the machine learning algorithms for COVID-19 case analysis

S Tiwari, P Chanak, SK Singh - IEEE Transactions on Artificial …, 2022 - ieeexplore.ieee.org
The purpose of this article is to see how machine learning (ML) algorithms and applications
are used in the COVID-19 inquiry and for other purposes. The available traditional methods …