Ongoing and planned studies using National Institute for Health Research (NIHR) Health Informatics Collaborative (HIC) Hepatitis B virus dataset
| Studies . | Goals . |
|---|---|
| HBV treatment eligibility and coverage | To assess HBV treatment eligibility and coverage of patients in this cohort, as well as to investigate which NICE treatment criteria and patient characteristics are associated with odds of receiving or not receiving treatment |
| Early prediction of HBsAg loss | To apply advanced machine learning techniques to predict HBsAg loss and determine key factors associated with this endpoint |
| HCC incidence and associated factors | To investigate factors affecting the incidence of HCC in patients with viral hepatitis |
| HCC identification | To develop a natural language processing (NLP) pipeline to automatically identify HCC from imaging reports |
| Metabolic factors and CHB outcomes | To explore the association between metabolic risk factors and CHB outcomes |
| HBV treatment failure risk prediction | To investigate virological suppression patterns and predict the risk of not suppressing or rebound viraemia in chronic HBV patients with antiviral treatment |
| Studies . | Goals . |
|---|---|
| HBV treatment eligibility and coverage | To assess HBV treatment eligibility and coverage of patients in this cohort, as well as to investigate which NICE treatment criteria and patient characteristics are associated with odds of receiving or not receiving treatment |
| Early prediction of HBsAg loss | To apply advanced machine learning techniques to predict HBsAg loss and determine key factors associated with this endpoint |
| HCC incidence and associated factors | To investigate factors affecting the incidence of HCC in patients with viral hepatitis |
| HCC identification | To develop a natural language processing (NLP) pipeline to automatically identify HCC from imaging reports |
| Metabolic factors and CHB outcomes | To explore the association between metabolic risk factors and CHB outcomes |
| HBV treatment failure risk prediction | To investigate virological suppression patterns and predict the risk of not suppressing or rebound viraemia in chronic HBV patients with antiviral treatment |
This list is not exhaustive, and more studies will be added over time.
HBV, hepatitis B virus; NICE, National Institute for Health and Care Excellence; HBsAg, hepatitis B surface antigen; HCC, hepatocellular carcinoma; CHB, chronic hepatitis B virus.
Ongoing and planned studies using National Institute for Health Research (NIHR) Health Informatics Collaborative (HIC) Hepatitis B virus dataset
| Studies . | Goals . |
|---|---|
| HBV treatment eligibility and coverage | To assess HBV treatment eligibility and coverage of patients in this cohort, as well as to investigate which NICE treatment criteria and patient characteristics are associated with odds of receiving or not receiving treatment |
| Early prediction of HBsAg loss | To apply advanced machine learning techniques to predict HBsAg loss and determine key factors associated with this endpoint |
| HCC incidence and associated factors | To investigate factors affecting the incidence of HCC in patients with viral hepatitis |
| HCC identification | To develop a natural language processing (NLP) pipeline to automatically identify HCC from imaging reports |
| Metabolic factors and CHB outcomes | To explore the association between metabolic risk factors and CHB outcomes |
| HBV treatment failure risk prediction | To investigate virological suppression patterns and predict the risk of not suppressing or rebound viraemia in chronic HBV patients with antiviral treatment |
| Studies . | Goals . |
|---|---|
| HBV treatment eligibility and coverage | To assess HBV treatment eligibility and coverage of patients in this cohort, as well as to investigate which NICE treatment criteria and patient characteristics are associated with odds of receiving or not receiving treatment |
| Early prediction of HBsAg loss | To apply advanced machine learning techniques to predict HBsAg loss and determine key factors associated with this endpoint |
| HCC incidence and associated factors | To investigate factors affecting the incidence of HCC in patients with viral hepatitis |
| HCC identification | To develop a natural language processing (NLP) pipeline to automatically identify HCC from imaging reports |
| Metabolic factors and CHB outcomes | To explore the association between metabolic risk factors and CHB outcomes |
| HBV treatment failure risk prediction | To investigate virological suppression patterns and predict the risk of not suppressing or rebound viraemia in chronic HBV patients with antiviral treatment |
This list is not exhaustive, and more studies will be added over time.
HBV, hepatitis B virus; NICE, National Institute for Health and Care Excellence; HBsAg, hepatitis B surface antigen; HCC, hepatocellular carcinoma; CHB, chronic hepatitis B virus.
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