Suchergebnisse - "Jia, Ruiqi"

PubPharm (19)

1

Unveiling the variability in cadmium accumulation and tolerance characteristics : a comparative study of Basma and Yunyan 87 tobacco varieties

enthalten in: Environmental technology | 2024

von Guo, Z. | Zhu, J. | Zheng, Y. | +6

2

Mechanisms of the novel pesticide sodium dodecyl benzene sulfonate in the mitigation of protozoan ciliated pathogens during microalgal cultivation

enthalten in: Marine pollution bulletin | 2024

von Sun, G. | Jia, R. | Zhang, Y. | +7

3

Physiological and transcriptomic responses of seawater halobios to micro/nano-scale polystyrene-cadmium exposure in a marine food web

enthalten in: Environmental pollution (Barking, Essex : 1987) | 2024

von Zhang, Y. | Jia, R. | Wang, Y. | +4

4

Post-endovascular treatment, blood-brain barrier disruption, predicts patient outcomes better than pre-treatment status

enthalten in: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology | 2024

von Zhai, H. | Li, Y. | Jia, R. | +4

5

Toxic effects on ciliates under nano-/micro-plastics coexist with silver nanoparticles

enthalten in: Journal of hazardous materials | 2024

von Jia, R. | Zhang, Y. | Wang, Y. | +3

6

Application of Shouwu Yizhi prescription in decubation of patients with ischemic stroke

enthalten in: Biotechnology & genetic engineering reviews | 2023

von Chen, C. | Cheng, G. | Jia, R. | +3

7

A New Time-Window Prediction Model For Traumatic Hemorrhagic Shock Based on Interpretable Machine Learning

enthalten in: Shock (Augusta, Ga.) | 2022

von Zhao, Y. | Jia, L. | Jia, R. | +15

8

Intelligent monitoring and early warning system for traumatic hemorrhagic shock

enthalten in: Europäisches Patentamt | 2021

von LI JING | LI TANSHI | JIA LIJING | +6

9

New coronal pneumonia patient outcome prediction method based on interpretable machine learning algorithm

enthalten in: Europäisches Patentamt | 2021

von JIA LIJING | LI JING | CHEN WEI | +7

10

An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19

enthalten in: Scientific reports | 2021

von Jia, L. | Wei, Z. | Zhang, H. | +15