Hirad Hosseini

Hirad Hosseini

B.S./M.S. Quantitative & Computational Biology at University of Southern California.

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

publications

Screening Patients at Risk of Age-Related Fragility Vertebral Fracture in the General Population Using Multiple-Row Detector Quantitative Computed Tomography With Chest or Heart Scan

Published in Journal of Cardiovascular Computed Tomography, 2020

Investigated the prevalence of vertebral fractures (VFs) across nearly 3500 patients (1730 F) via observation of morphological deformities of spinal bodies in CT chest or heart scans. Patients were separated into five distinct age ranges: 20-40, 40-50, 50-60, 60-70 and >80 years. The prevalence of VF increased across all age ranges, with the most profound increase in VF frequency observed in the fifth age range (>80 years). This study also corroborated the diagnostic value of chest CT scan as a relatively cheap, low-radiation approach for estimating VFs.

Recommended citation: Mao et al. (2020). "Screening Patients at Risk of Age-Related Fragility Vertebral Fracture in the General Population Using Multiple-Row Detector Quantitative Computed Tomography with Chest or Heart Scan." Journal of Cardiovascular Computed Tomography. 14(3). http://hiradhosseini.github.io/files/paper2.pdf

Comparison In Quantitative Coronary Calcified Plaque Burden Between Filter Back Projection and Iterative Reconstruction Algorithm Using Scan With Various Exposure Dosage

Published in Journal of Cardiovascular Computed Tomography, 2020

Observed a statistically significant decrease in Agatston score and plaque burden volume when comparing Iterative Reconstruction (IR) algorithm scans to Filter Back Projection (FBP) scans across all five groups with varying electric current products ranging from 17 to 75 mAs. This finding suggests the necessity of calibrating coronary calcium scores derived from IR scans based on exposure dosage.

Recommended citation: Mao et al. (2020). "Comparison In Quantitative Coronary Calcified Plaque Burden Between Filter Back Projection and Iterative Reconstruction Algorithm Using Scan With Various Exposure Dosage." Journal of Cardiovascular Computed Tomography. 14(3). http://hiradhosseini.github.io/files/paper1.pdf

Both Vertebral Bone Mineral Density and Presence or Growth of Schmorls Node Are Important Pedictors for Future Vertebral Fracture

Published in Journal of Cardiovascular Computed Tomography, 2020

Investigated the relationship between thoracic vertebral bone mineral density (BMD), Schmorls Node presence/growth and presence of vertebral fracture in 3409 consecutive patients (1730 F) who underwent non-contrast heart and chest CT scans. Schmorls Node prevalence increased progressively with advanced age and was inversely related to BMD. Both Schmorls Node presence and vertebral BMD were shown to be associated with VF.

Recommended citation: Mao et al. (2020). "Both Vertebral Bone Mineral Density and Presence or Growth of Schmorls Node Are Important Pedictors for Future Vertebral Fracture." Journal of Cardiovascular Computed Tomography. 14(3). http://hiradhosseini.github.io/files/paper3.pdf

Thoracic QCT From Heart Scan Can Monitor Age-Related Bone Loss Sensitively: A Comparing with DXA and QCT Study

Published in Journal of Cardiovascular Computed Tomography, 2020

Investigated the diagnostic value of BMD-aimed lumbnar CT scan, hip and lumbar DXA scan, and heart CT scan to measure coronary calcified plaque burden for 457 asymptomatic patients (197 F). Thoracic and lumbar QCT both demonstrated greater sensitivity to age-related bone loss than hip DXA. Therefore, thoracic QCT derived from existing lung or heart CT scans can provide a more sensitive assessment of bone loss than DXA, barring additional radiation or costs.

Recommended citation: Mao et al. (2020). "Thoracic QCT From Heart Scan Can Monitor Age-Related Bone Loss Sensitively: A Comparing with DXA and QCT Study" Journal of Cardiovascular Computed Tomography. 14(3). http://hiradhosseini.github.io/files/paper5.pdf

Cryptococcus gattii and its Distinctive Yeast Morphology in Cerebrospinal Fluid Cytology

Published in Journal of Pathology and Infectious Diseases, 2020

Case report involving 30-year-old immunocompetent male with C. gattii induced cryptococcosis. Cytological evaluation of CSF revealed a distinctive morphology for C. gattii, allowing for diagnostic differentiation with C. neoformans.

Recommended citation: Hosseini et al. (2020). "Cryptococcus gattii and its Distinctive Yeast Morphology in Cerebrospinal Fluid Cytology" Journal of Pathology and Infectious Diseases. 3(1). http://hiradhosseini.github.io/files/paper6.pdf

Ability of Assessing Osteoporosis and Osteoporotic Vertebral Fracture in the General Population When Using Thoracic Quantitative Computed Tomography: A Comparison Study Between Low-Dose Thoracic Quantitative Computed Tomography and Lumbar Dual-Energy X-Ray Absorptiometry

Published in Journal of Cardiovascular Computed Tomography, 2021

Compared thoracic Quantitative Computed Tomography (tQCT) and lumbar dual X-ray absorptiometry (IDXA) for predicting age-related osteoporosis and osteoporotic vertebral fracture in 360 patients (46 with VF). tQCT demonstrated superior sensitivity for predicting both osteoporosis and osteoporotic VF risk.

Recommended citation: Mao et al. (2021). "Ability of Assessing Osteoporosis and Osteoporotic Vertebral Fracture in the General Population When Using Thoracic Quantitative Computed Tomography: A Comparison Study Between Low-Dose Thoracic Quantitative Computed Tomography and Lumbar Dual-Energy X-Ray Absorptiometry." Journal of Cardiovascular Computed Tomography. 15(3). http://hiradhosseini.github.io/files/paper4.pdf

Anti-Hypertensive Medications Can Reduce the Vertebral Bone Mineral Loss in Aging Hypertensive Patients

Published in Journal of Cardiovascular Computed Tomography, 2021

Conducted multi-row detector CT heart scan for obtaining coronary plaque score for 2267 patients (age 65+-11, 1231 F) with hypertension and anti-hypertensive therapy and matching control group. A significant higher tBMD was found in patients using anti-hypertensive therapy as compared to the normotensive population. Therefore, anti-hypertensive drugs can reduce the rate of vertebral bone mineral loss, with specific medication class being investigated.

Recommended citation: Mao et al. (2021). "Anti-Hypertensive Medications Can Reduce the Vertebral Bone Mineral Loss in Aging Hypertensive Patients" Journal of Cardiovascular Computed Tomography. 15(3). http://hiradhosseini.github.io/files/paper7.pdf

Digital Twin Cities for Air Quality Simulation

Published in American Geophysical Union Fall 2022 Meeting, 2022

Air pollution has become one of the most pressing challenges facing policy-makers and researchers worldwide. Governments are reckoning with the human, environmental, and economic impacts of air quality-related damages. In 2019, air quality-related issues caused over 7 million air-quality-related deaths, and nearly $8.1 trillion in health-related economic damages. Addressing these issues will require major infrastructural investment and new initiatives from policy-makers and legislators.

Recommended citation: [1]Hosseini, H., “Digital Twin Cities for Air Quality Simulation”, vol. 2022, 2022. https://ui.adsabs.harvard.edu/abs/2022AGUFMIN41B..02H/abstract

Global High-Resolution PM2. 5 Prediction Applying Multisource Big Data through Deep Convolutional LSTM

Published in American Geophysical Union Fall 2022 Meeting, 2022

Ambient air pollution is a silent killer. It contributes to 7 million deaths annually and accounts for a 2.2 year reduction in the average global life expectancy. Moreover, more than one in four deaths of children under the age of 5 can be directly linked to the harmful effects of air pollution. Air pollution is most detrimental in highly urbanized metropolitan areas, and since it is projected that more than two thirds of the world population will live in urban areas by 2050, it is imperative we mitigate the severe effects of this harmful global threat.

Recommended citation: [1]Muthukumar, P., “Global High-Resolution PM2.5 Prediction Applying Multisource Big Data through Deep Convolutional LSTM”, vol. 2022, 2022. https://ui.adsabs.harvard.edu/abs/2022AGUFMIN41B..03M/abstract

Multi-Pollutant Ground-level Air Pollution Prediction through Deep MeteoGCN-ConvLSTM

Published in 2022 International Conference on Computational Science and Computational Intelligence (CSCI), 2022

Air pollution is the fourth-largest threat to human health. The harmful effects of air pollutants have cost the global economy nearly $3 trillion. It is imperative that a solution for mitigating the harmful effects of the most pervasive ground-level air pollutants—carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter 2.5 (PM2.5)—is implemented, especially in urban areas. Recent advances in deep learning, such as the Convolutional Long Short Term Memory (ConvLSTM) architecture, are capable of learning complex spatiotemporal patterns with multisource data. We propose a novel sequential encoder-decoder ConvLSTM architecture capable of predicting hourly CO, NO, NO₂, O₃, and PM2.5 levels spatially and continuously over Los Angeles. Our model utilizes multisource satellite imagery collected from the ESA Tropospheric Monitoring…

Recommended citation: P. Muthukumar et al., "Multi-Pollutant Ground-level Air Pollution Prediction through Deep MeteoGCN-ConvLSTM," 2022 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA, 2022, pp. 26-34, doi: 10.1109/CSCI58124.2022.00012. https://ieeexplore.ieee.org/abstract/document/10216524

Predicting Atmospheric Air Pollution: A Convolutional-Transformer Approach for Spatial and Temporal Analysis of PM2.5

Published in 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE), 2023

6.7 million premature deaths occur annually due to household and ambient air pollution. Air pollution affects individuals globally and can be derived from a variety of factors including household cooking fuel, motor vehicles, industrial practices, and natural fires. To tackle this global crisis, our research focuses on understanding the spatial and temporal patterns between air pollutants to predict future levels of air pollutants. Our approach uses a novel deep learning methodology that involves a spatiotemporal Convolutional-Transformer architecture (ConvTransformer).

Recommended citation: J. Kalra et al., "Predicting Atmospheric Air Pollution: A Convolutional- Transformer Approach for Spatial and Temporal Analysis of PM2.5," 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE), Las Vegas, NV, USA, 2023, pp. 1589-1596, doi: 10.1109/CSCE60160.2023.00261. https://ieeexplore.ieee.org/abstract/document/10487308

talks

When Two Pandemics Collide: Obesity and COVID-19

Published:

Selected as speaker for the Lundquist Institute Summer High Schools Fellows Program. Discussed the interaction between obesity and COVID-19 susceptibility via the Jak-STAT pathway.

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.