Tabassom Sedighi
Biographic Data
| ID | 7858116 |
|---|---|
| NAME | Tabassom Sedighi |
| GIVEN NAMES | Tabassom |
| FAMILY NAME | Sedighi |
| SIGNATURE | SEDIGHI T |
| AFFILIATIONS | Cranfield University |
| ORCID | 0000-0003-1794-4342 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for Covid-19 Inpatients
The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and c…
Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms
Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk area…
Economic Evaluation of Mental Health Effects of Flooding Using Bayesian Networks
The appraisal of appropriate levels of investment for devising flooding mitigation and to support recovery interventions is a complex and challenging task. Evaluation must account for social, political, environmental and other conditions, such as flood state expectations and local priorities. The evaluation method should be able to quickly identify evolving investment needs as the incidence and magnitude of flood events continue to grow. Quantifi…
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Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for Covid-19 Inpatients
The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and c…
Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms
Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk area…
Economic Evaluation of Mental Health Effects of Flooding Using Bayesian Networks
The appraisal of appropriate levels of investment for devising flooding mitigation and to support recovery interventions is a complex and challenging task. Evaluation must account for social, political, environmental and other conditions, such as flood state expectations and local priorities. The evaluation method should be able to quickly identify evolving investment needs as the incidence and magnitude of flood events continue to grow. Quantifi…
Business (2 works) · Computer Science (2 works) · Medicine (2 works) · Risk analysis (engineering (2 works) · Agricultural risk and resilience (1 work) · Animal Disease Management and Epidemiology (1 work) · Anxiety (1 work) · Artificial Intelligence (1 work) · Bayesian network (1 work) · Bioinformatics (1 work)