The efficacy and safety of Favipiravir in treatment of COVID-19: a systematic review and meta-analysis of clinical trials

S Hassanipour, M Arab-Zozani, B Amani… - Scientific reports, 2021‏ - nature.com
The novel coronavirus outbreak began in late December 2019 and rapidly spread
worldwide, critically impacting public health systems. A number of already approved and …

[HTML][HTML] Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews

A Martinez-Millana, A Saez-Saez… - International Journal of …, 2022‏ - Elsevier
Background Artificial intelligence is fueling a new revolution in medicine and in the
healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there …

TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model

Y Wang, T Fu, Y Xu, Z Ma, H Xu, B Du, Y Lu… - ACM Transactions on …, 2024‏ - dl.acm.org
Clinical trials are indispensable for medical research and the development of new
treatments. However, clinical trials often involve thousands of participants and can span …

Predictive performance of machine and statistical learning methods: Impact of data-generating processes on external validity in the “large N, small p” setting

PC Austin, FE Harrell Jr… - Statistical methods in …, 2021‏ - journals.sagepub.com
Machine learning approaches are increasingly suggested as tools to improve prediction of
clinical outcomes. We aimed to identify when machine learning methods perform better than …

[HTML][HTML] Benefits of information technology in healthcare: artificial intelligence, internet of things, and personal health records

H Chang, JY Choi, J Shim, M Kim… - Healthcare Informatics …, 2023‏ - synapse.koreamed.org
Objectives Systematic evaluations of the benefits of health information technology (HIT) play
an essential role in enhancing healthcare quality by improving outcomes. However, there is …

[HTML][HTML] Comparison of severity of illness scores and artificial intelligence models that are predictive of intensive care unit mortality: meta-analysis and review of the …

C Barboi, A Tzavelis, LNQ Muhammad - JMIR Medical …, 2022‏ - mededu.jmir.org
Background: Severity of illness scores—Acute Physiology and Chronic Health Evaluation,
Simplified Acute Physiology Score, and Sequential Organ Failure Assessment—are current …

Sensor data fusion for a mobile robot using neural networks

AJ Barreto-Cubero, A Gómez-Espinosa… - Sensors, 2021‏ - mdpi.com
Mobile robots must be capable to obtain an accurate map of their surroundings to move
within it. To detect different materials that might be undetectable to one sensor but not others …

[PDF][PDF] Classification performance of neural networks versus logistic regression models: evidence from healthcare practice

RW Issitt, M Cortina-Borja, W Bryant, S Bowyer… - Cureus, 2022‏ - cureus.com
Abstract Machine learning encompasses statistical approaches such as logistic regression
(LR) through to more computationally complex models such as neural networks (NN). The …

Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice

S Imai, Y Takekuma, H Kashiwagi, T Miyai… - PLoS …, 2020‏ - journals.plos.org
Artificial neural networks are the main tools for data mining and were inspired by the human
brain and nervous system. Studies have demonstrated their usefulness in medicine …

Construction of a machine learning-based artificial neural network for discriminating PANoptosis related subgroups to predict prognosis in low-grade gliomas

GF Chen, ZM He, W Jiang, LL Li, B Luo, XY Wang… - Scientific Reports, 2022‏ - nature.com
The poor prognosis of gliomas necessitates the search for biomarkers for predicting clinical
outcomes. Recent studies have shown that PANoptosis play an important role in tumor …