Mohammad Kashkooli
Biographic Data
| ID | 7954706 |
|---|---|
| NAME | Mohammad Kashkooli |
| GIVEN NAMES | Mohammad |
| FAMILY NAME | Kashkooli |
| SIGNATURE | KASHKOOLI M |
| AFFILIATIONS | Shiraz University of Medical Sciences |
| ORCID | 0000-0002-3009-5544 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Heavy metal biomarkers and their impact on hearing loss risk
Background: Exposure to heavy metals has been implicated in adverse auditory health outcomes, yet the precise relationships between heavy metal biomarkers and hearing status remain underexplored. This study leverages a machine learning framework to investigate these associations, offering a novel approach to understanding the interplay between environmental exposures and hearing loss. Methods: We conducted a retrospective cross-sectional analysis…
A systems biology approach for discovering the cellular and molecular aspects of psychogenic non-epileptic seizure
This study was the first to gather the biochemicals associated with PNES. Multiple components and pathways and several psychiatric diseases associated with PNES, and some brain regions that could be altered during PNES were suggested, which should be confirmed in further studies. Altogether, these findings could be used in future molecular research on PNES patients
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A systems biology approach for discovering the cellular and molecular aspects of psychogenic non-epileptic seizure
This study was the first to gather the biochemicals associated with PNES. Multiple components and pathways and several psychiatric diseases associated with PNES, and some brain regions that could be altered during PNES were suggested, which should be confirmed in further studies. Altogether, these findings could be used in future molecular research on PNES patients
Heavy metal biomarkers and their impact on hearing loss risk
Background: Exposure to heavy metals has been implicated in adverse auditory health outcomes, yet the precise relationships between heavy metal biomarkers and hearing status remain underexplored. This study leverages a machine learning framework to investigate these associations, offering a novel approach to understanding the interplay between environmental exposures and hearing loss. Methods: We conducted a retrospective cross-sectional analysis…
Medicine (2 works) · Audiology (1 work) · Bioinformatics (1 work) · Biology (1 work) · Bipolar disorder (1 work) · Cell Biology (1 work) · Computer Science (1 work) · Epilepsy (1 work) · Genetic Neurodegenerative Diseases (1 work) · Genetics (1 work)