Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My NCBI Filters

Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2016 1
2017 1
2019 2
2020 4
2021 6
2023 2
2024 1

Text availability

Article attribute

Article type

Publication date

Search Results

15 results

Results by year

Filters applied: . Clear all
Page 1
Achillea spp.: A comprehensive review on its ethnobotany, phytochemistry, phytopharmacology and industrial applications.
Salehi B, Selamoglu Z, Sevindik M, Fahmy NM, Al-Sayed E, El-Shazly M, Csupor-Löffler B, Csupor D, Yazdi SE, Sharifi-Rad J, Arserim-Uçar DK, Arserim EH, Karazhan N, Jahani A, Dey A, Azadi H, Vakili SA, Sharopov F, Martins N, Büsselberg D. Salehi B, et al. Among authors: jahani a. Cell Mol Biol (Noisy-le-grand). 2020 Jun 25;66(4):78-103. Cell Mol Biol (Noisy-le-grand). 2020. PMID: 32583790 Review.
Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran).
Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y. Shams SR, et al. Among authors: jahani a. Environ Pollut. 2023 Dec 1;338:122623. doi: 10.1016/j.envpol.2023.122623. Epub 2023 Oct 6. Environ Pollut. 2023. PMID: 37806430
Corrigendum to "Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forecasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)" [Environ. Pollut., 338 (2023) 122623].
Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y. Shams SR, et al. Among authors: jahani a. Environ Pollut. 2024 Feb 1;342:123102. doi: 10.1016/j.envpol.2023.123102. Epub 2023 Dec 12. Environ Pollut. 2024. PMID: 38086164 No abstract available.
15 results