Jakov Zlodre
Biographic Data
| ID | 7230966 |
|---|---|
| NAME | Jakov Zlodre |
| GIVEN NAMES | Jakov |
| FAMILY NAME | Zlodre |
| SIGNATURE | ZLODRE J |
| AFFILIATIONS | Jakov Zlodre is with Oxford Health NHS Foundation Trust, Oxford, UK. Seena Fazel is with the Department of Psychiatry, University of Oxford, Oxford, UK. |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Identifying Predictors of Suicide in Severe Mental Illness
It is feasible to estimate suicide risk with the OxMIS tool using predictors identified in routine clinical records. Predictors could be extracted using natural language processing. However, electronic health records differ from other data sources, particularly for family history variables, which creates methodological challenges
All-Cause and External Mortality in Released Prisoners
Objectives. We systematically reviewed studies of mortality following release from prison and examined possible demographic and methodological factors associated with variation in mortality rates. Methods. We searched 5 computer-based literature indexes to conduct a systematic review of studies that reported all-cause, drug-related, suicide, and homicide deaths of released prisoners. We extracted and meta-analyzed crude death rates and standardiz…
No prominent works on this page.
All-Cause and External Mortality in Released Prisoners
Objectives. We systematically reviewed studies of mortality following release from prison and examined possible demographic and methodological factors associated with variation in mortality rates. Methods. We searched 5 computer-based literature indexes to conduct a systematic review of studies that reported all-cause, drug-related, suicide, and homicide deaths of released prisoners. We extracted and meta-analyzed crude death rates and standardiz…
Identifying Predictors of Suicide in Severe Mental Illness
It is feasible to estimate suicide risk with the OxMIS tool using predictors identified in routine clinical records. Predictors could be extracted using natural language processing. However, electronic health records differ from other data sources, particularly for family history variables, which creates methodological challenges
Medical emergency (1 work) · Medicine (1 work) · Mental health (1 work) · Mental Health and Psychiatry (1 work) · Mental Health Treatment and Access (1 work) · Mental illness (1 work) · Poison control (1 work) · Psychiatry (1 work) · Psychology (1 work) · Suicide and Self-Harm Studies (1 work)