From bdb781174f47fe246f8aa7bc97f3a5b27d8a43d2 Mon Sep 17 00:00:00 2001 From: Sammi Rosser <29951987+Bergam0t@users.noreply.github.com> Date: Wed, 23 Oct 2024 22:06:51 +0000 Subject: [PATCH] Experiments with author affiliation display Normalisation of schema that happens behind the scenes is causing endless problems and unexpected behaviours --- .quarto/preview/lock | 2 +- .quarto/xref/a290ceac | 2 +- .../previous_projects/projects_by_cohort.html | 319 ++++++++++++++++-- .../projects_by_methods.html | 8 +- .../projects_by_organisation.html | 4 +- .../projects_by_service_area.html | 4 +- docs/search.json | 6 +- docs/styles.css | 2 +- html/previous_projects/listing.ejs | 15 +- 9 files changed, 310 insertions(+), 52 deletions(-) diff --git a/.quarto/preview/lock b/.quarto/preview/lock index 979fdc5a..0347dc6f 100644 --- a/.quarto/preview/lock +++ b/.quarto/preview/lock @@ -1 +1 @@ -78088 \ No newline at end of file +10138 \ No newline at end of file diff --git a/.quarto/xref/a290ceac b/.quarto/xref/a290ceac index 208374ba..7df77d53 100644 --- a/.quarto/xref/a290ceac +++ b/.quarto/xref/a290ceac @@ -1 +1 @@ -{"entries":[],"headings":[]} \ No newline at end of file +{"headings":[],"entries":[]} \ No newline at end of file diff --git a/docs/previous_projects/projects_by_cohort.html b/docs/previous_projects/projects_by_cohort.html index 88d3f36b..ef5a7416 100644 --- a/docs/previous_projects/projects_by_cohort.html +++ b/docs/previous_projects/projects_by_cohort.html @@ -347,7 +347,7 @@

HSMA 5

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Using Discrete Event Simulation t
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A Discrete Event Simulation Model
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A Discrete Event Simulation Model
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-
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Discrete Event Simulation to mode
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Modelling the effect of complex d
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Modelling the effect of complex d
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@@ -545,7 +573,11 @@
Forecasting Demand – Investigat
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@@ -559,6 +591,9 @@
Forecasting Demand – Investigat
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@@ -586,7 +621,11 @@
Creating a tool to automatically
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Creating a tool to automatically
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@@ -631,7 +673,11 @@
Developing a tool to assess inequ
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Developing a tool to assess inequ
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@@ -670,7 +719,11 @@
Using Machine Learning to estimat
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Using Machine Learning to estimat
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@@ -715,7 +771,11 @@
Modelling the location of neonata
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@@ -729,6 +789,9 @@
Modelling the location of neonata
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@@ -756,7 +819,11 @@
Network Analysis of diagnostic pr
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Network Analysis of diagnostic pr
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@@ -797,7 +867,11 @@
Using Natural Language Processing
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Using Natural Language Processing
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@@ -838,7 +915,11 @@
Understanding Excess Mortality in
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Understanding Excess Mortality in
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Investigating factors impacting N
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Investigating factors impacting N
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No matching items @@ -928,7 +1019,11 @@
The Effect of Booked Appointments -
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The Effect of Booked Appointments
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South East Regional Covid 19 Vacc -
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South East Regional Covid 19 Vacc
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Use of Discrete Event Simulation -
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Use of Discrete Event Simulation
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Using DES to Improve Flow through -
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Using DES to Improve Flow through
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Discrete Event Simulation of Cogn -
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Discrete Event Simulation of Cogn
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Use Of Discrete Event Simulation -
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Use Of Discrete Event Simulation
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Discrete Event Simulation to Impr -
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Discrete Event Simulation to Impr
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Forecasting Demand and Length of -
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Forecasting Demand and Length of
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Meeting the demand of 111 for pri -
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Meeting the demand of 111 for pri
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Using Machine Learning to Predict -
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Using Machine Learning to Predict
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The role of Patient Initiated Fol -
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The role of Patient Initiated Fol
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@@ -1291,7 +1459,11 @@
Predicting Non-Elective Admission -
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Predicting Non-Elective Admission
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Predicting Violent Incidents on M -
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Predicting Violent Incidents on M
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Reducing Travel Times to Treatmen -
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Reducing Travel Times to Treatmen
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Developing a Service Planning Dec -
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Developing a Service Planning Dec
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Spatial Modelling of Violent Crim -
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Spatial Modelling of Violent Crim
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No matching items @@ -1460,7 +1663,11 @@
What are they saying about us? An -
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What are they saying about us? An
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Generating a richer understanding -
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Generating a richer understanding
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Modelling strategies to reduce th -
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Modelling strategies to reduce th
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Developing a generic vaccination -
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Developing a generic vaccination
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Exploring the use of Machine Lear -
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Exploring the use of Machine Lear
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Simulation modelling to test prop -
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Simulation modelling to test prop
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No matching items diff --git a/docs/previous_projects/projects_by_methods.html b/docs/previous_projects/projects_by_methods.html index 2818180a..e5402474 100644 --- a/docs/previous_projects/projects_by_methods.html +++ b/docs/previous_projects/projects_by_methods.html @@ -729,7 +729,7 @@
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diff --git a/docs/search.json b/docs/search.json index 1aabc51d..286f7886 100644 --- a/docs/search.json +++ b/docs/search.json @@ -473,21 +473,21 @@ "href": "previous_projects/projects_by_cohort.html#hsma-5", "title": "HSMA Projects by Cohort", "section": "HSMA 5", - "text": "HSMA 5\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n Using Discrete Event Simulation to model the bottlenecks in the Acute Medical Unit pathway\n \n\n \n \n In this project, a computer simulation of the acute medical pathway in a Devon trust was created, along with an interactive tool allowing parameters such as the staffing levels to be changed. This allowed staff to explore the optimum levels of resourcing, enabling risk-free testing of staffing and resource changes before committing to these changes in the real-world.\n\n \n \n\n \n \n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n A Discrete Event Simulation Model to reduce Rheumatology waiting times in Dorset\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation to model elective surgery pathways\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling the effect of complex discharge delays on acute performance\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Forecasting Demand – Investigating approaches to forecast clock starts\n \n\n \n \n \n\n \n \n \n Forecasting\n \n Prophet\n \n ARIMA\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Creating a tool to automatically generate health equity audits for Community Diagnostic Centres\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Automation\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a tool to assess inequalities and demographic coverage of service locations\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Mapping\n \n Travel Times\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Machine Learning to estimate inequities in access to hospital procedures\n \n\n \n \n \n\n \n \n \n Machine Learning\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling the location of neonatal critical care units in North West England\n \n\n \n \n \n\n \n \n \n Mapping\n \n Location Optimization\n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Network Analysis of diagnostic procedures in A&E setting\n \n\n \n \n \n\n \n \n \n Network Analysis\n \n Plotly Dash\n \n \n \n\n \n\n \n \n \n \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Natural Language Processing to detect drug related content within free text\n \n\n \n \n \n\n \n \n \n Natural Language Processing\n \n Named Entity Recognition\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Understanding Excess Mortality in Dorset\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Forecasting\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Investigating factors impacting NHS workforce retention\n \n\n \n \n \n\n \n \n \n Plotly Dash\n \n Regression\n \n Machine Learning\n \n \n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n\n\nNo matching items" + "text": "HSMA 5\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n Using Discrete Event Simulation to model the bottlenecks in the Acute Medical Unit pathway\n \n\n \n \n In this project, a computer simulation of the acute medical pathway in a Devon trust was created, along with an interactive tool allowing parameters such as the staffing levels to be changed. This allowed staff to explore the optimum levels of resourcing, enabling risk-free testing of staffing and resource changes before committing to these changes in the real-world.\n\n \n \n\n \n \n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n A Discrete Event Simulation Model to reduce Rheumatology waiting times in Dorset\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation to model elective surgery pathways\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling the effect of complex discharge delays on acute performance\n \n\n \n \n \n\n \n \n \n Discrete Event Simulation\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Forecasting Demand – Investigating approaches to forecast clock starts\n \n\n \n \n \n\n \n \n \n Forecasting\n \n Prophet\n \n ARIMA\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Creating a tool to automatically generate health equity audits for Community Diagnostic Centres\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Automation\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a tool to assess inequalities and demographic coverage of service locations\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Mapping\n \n Travel Times\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Machine Learning to estimate inequities in access to hospital procedures\n \n\n \n \n \n\n \n \n \n Machine Learning\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling the location of neonatal critical care units in North West England\n \n\n \n \n \n\n \n \n \n Mapping\n \n Location Optimization\n \n Discrete Event Simulation\n \n Streamlit\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Network Analysis of diagnostic procedures in A&E setting\n \n\n \n \n \n\n \n \n \n Network Analysis\n \n Plotly Dash\n \n \n \n\n \n\n \n\n \n \n \n \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Natural Language Processing to detect drug related content within free text\n \n\n \n \n \n\n \n \n \n Natural Language Processing\n \n Named Entity Recognition\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Understanding Excess Mortality in Dorset\n \n\n \n \n \n\n \n \n \n Streamlit\n \n Forecasting\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Investigating factors impacting NHS workforce retention\n \n\n \n \n \n\n \n \n \n Plotly Dash\n \n Regression\n \n Machine Learning\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n\n\nNo matching items" }, { "objectID": "previous_projects/projects_by_cohort.html#hsma-4", "href": "previous_projects/projects_by_cohort.html#hsma-4", "title": "HSMA Projects by Cohort", "section": "HSMA 4", - "text": "HSMA 4\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n The Effect of Booked Appointments on Waiting Times at Urgent Treatment Centres\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n South East Regional Covid 19 Vaccination Demand & Capacity Modelling\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Use of Discrete Event Simulation to Tackle Long Waits and a Growing Backlog for Children Requiring Neuro Development Assessment (Autism and ADHD)\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using DES to Improve Flow through an Acute Medicine Assessment Pathway\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation of Cognitive Behavioural Therapy Pathway in an IAPT Service\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Use Of Discrete Event Simulation (DES) to reduce delays in Cancer Diagnosis & Treatment\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation to Improve Flow and Performance in the Urgent Treatment Centre\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Forecasting Demand and Length of Stay in the Emergency Department\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Meeting the demand of 111 for primary care services\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Machine Learning to Predict Hospital Admissions and Length of Stay for Respiratory Conditions\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n The role of Patient Initiated Follow-up (PIFU) and ‘Digital Outpatients’ in Supporting the Elective Recovery - Can We Better Size Potential for Clearing the Backlog?\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Predicting Non-Elective Admissions\n \n\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Predicting Violent Incidents on Mental Health Inpatient Units\n \n\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Reducing Travel Times to Treatment for Cardiac Patients in the South East of England\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a Service Planning Decision Support Tool to Tackle Inequalities and Minimise Carbon Output\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Spatial Modelling of Violent Crime to Support Strategic Analysis\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n\n\nNo matching items" + "text": "HSMA 4\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n The Effect of Booked Appointments on Waiting Times at Urgent Treatment Centres\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n South East Regional Covid 19 Vaccination Demand & Capacity Modelling\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Use of Discrete Event Simulation to Tackle Long Waits and a Growing Backlog for Children Requiring Neuro Development Assessment (Autism and ADHD)\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using DES to Improve Flow through an Acute Medicine Assessment Pathway\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation of Cognitive Behavioural Therapy Pathway in an IAPT Service\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Use Of Discrete Event Simulation (DES) to reduce delays in Cancer Diagnosis & Treatment\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Discrete Event Simulation to Improve Flow and Performance in the Urgent Treatment Centre\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Forecasting Demand and Length of Stay in the Emergency Department\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Meeting the demand of 111 for primary care services\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Using Machine Learning to Predict Hospital Admissions and Length of Stay for Respiratory Conditions\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n The role of Patient Initiated Follow-up (PIFU) and ‘Digital Outpatients’ in Supporting the Elective Recovery - Can We Better Size Potential for Clearing the Backlog?\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Predicting Non-Elective Admissions\n \n\n \n\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Predicting Violent Incidents on Mental Health Inpatient Units\n \n\n \n\n \n\n \n\n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Reducing Travel Times to Treatment for Cardiac Patients in the South East of England\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a Service Planning Decision Support Tool to Tackle Inequalities and Minimise Carbon Output\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Spatial Modelling of Violent Crime to Support Strategic Analysis\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n\n\nNo matching items" }, { "objectID": "previous_projects/projects_by_cohort.html#hsma-3", "href": "previous_projects/projects_by_cohort.html#hsma-3", "title": "HSMA Projects by Cohort", "section": "HSMA 3", - "text": "HSMA 3\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n What are they saying about us? An AI tool to determine the sentiment of tweets to police forces across the country, and what people are talking about\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Generating a richer understanding of relationships in crime data in order to identify opportunities to safeguard individuals and families\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling strategies to reduce the elective backlog in hip surgery\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a generic vaccination service model for the COVID-19 pandemic and beyond\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Exploring the use of Machine Learning and Natural Language Processing to teach a machine to predict whether a patient is likely to be imminently admitted to hospital based on GP data and clues in GP notes\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Simulation modelling to test proposed models of pediatric critical care in South West England\n \n\n \n \n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n\n\nNo matching items" + "text": "HSMA 3\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n What are they saying about us? An AI tool to determine the sentiment of tweets to police forces across the country, and what people are talking about\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Generating a richer understanding of relationships in crime data in order to identify opportunities to safeguard individuals and families\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Modelling strategies to reduce the elective backlog in hip surgery\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Developing a generic vaccination service model for the COVID-19 pandemic and beyond\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Exploring the use of Machine Learning and Natural Language Processing to teach a machine to predict whether a patient is likely to be imminently admitted to hospital based on GP data and clues in GP notes\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n Code \n \n Website \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Simulation modelling to test proposed models of pediatric critical care in South West England\n \n\n \n \n \n\n \n\n \n\n \n\n \n \n \n \n \n Video \n \n \n \n \n \n \n \n \n \n\n\nNo matching items" }, { "objectID": "previous_projects/hsma_5/h5_workforce_turnover_drivers/index.html", diff --git a/docs/styles.css b/docs/styles.css index eef19588..3aa48165 100644 --- a/docs/styles.css +++ b/docs/styles.css @@ -123,7 +123,7 @@ .project-link-listing-button { background-color: #8a0000; /* Grey background */ color: rgb(218, 218, 218); /* Off-White text */ - border: 2px solid rgb(211, 210, 210); /* Off-White border */ + border: 2px solid rgb(218, 218, 218); /* Off-White border */ padding: 5px 5px; /* Padding for better clickability */ margin: 2px 0px; font-size: 11px; /* Font size */ diff --git a/html/previous_projects/listing.ejs b/html/previous_projects/listing.ejs index ff09db84..d254d926 100644 --- a/html/previous_projects/listing.ejs +++ b/html/previous_projects/listing.ejs @@ -29,7 +29,17 @@

<% } %> -
+ + +
@@ -42,6 +52,9 @@ <% } %>
+ + + <% } %>
```