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Nanomaterials Versus Ambient Ultrafine Particles: An Opportunity to Exchange Toxicology Knowledge
Conclusion: There is now an opportunity to apply knowledge from NM toxicology and use it to better inform PM health risk research and vice versa. https://doi.org/10.1289/EHP424 Received: 17 December 2015 Revised: 12 August 2016 Accepted: 30 August 2016 Published: 10 October 2017 Address correspondence to V. Stone, School of Life Sciences, Heriot-Watt University, Edinburgh, UK. Telephone: +44 131 451 3460. Email: v.stone@hw.ac.uk V.S. currently receives grant funding from Byk Altana and from The European Ceramic Fibre Industry Association (ECFIA). In the past, V.S. has received funding from Unilever and GlaxoSmithKline....
Source: EHP Research - October 10, 2017 Category: Environmental Health Authors: Daniil Lyalko Tags: Review Source Type: research

Using Artificial Intelligence to Develop a Multivariate Model with a Machine Learning Model to Predict Complications in Mexican Diabetic Patients without Arterial Hypertension (National Nested Case-Control Study): Metformin and Elevated Normal Blood Pressure Are Risk Factors, and Obesity Is Protective
In conclusion, the results we have obtained show that artificial intelligence is a powerful and feasible tool to use for this type of study. However, we suggest that more studies be conducted to verify and elaborate upon our findings.PMID:36846513 | PMC:PMC9949947 | DOI:10.1155/2023/8898958
Source: Cancer Control - February 27, 2023 Category: Cancer & Oncology Authors: Sergio A Zaizar-Fregoso Agustin Lara-Esqueda Carlos M Hern ández-Suarez Josuel Delgado-Enciso Arturo Garcia-Nevares Luis M Canseco-Avila Jose Guzman-Esquivel Iram P Rodriguez-Sanchez Margarita L Martinez-Fierro Gabriel Ceja-Espiritu Hector Ochoa-D íaz-L Source Type: research