Richard Jackson - Big Data in Mental Health - 23rd July 2014
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Organised by the Bioinformatics group at the BRCMH, IoP, SLaM and Maudsley Digital, this symposium showcased talks regarding the important roles of big data in mental health biomedical research and treatments.
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Chris Hollis - Big Data in Mental Health - 23rd July 2014 - 1
MindTech is a NIHR Healthcare Technology Co-operative focused on accelerating the development and adoption of innovative mental healthcare technologies. It aims to transform service delivery, enhance the patient experience, and improve outcomes through needs-led technology development with partners like patients, industry, and researchers. MindTech focuses on clinical areas like mood disorders, neurodevelopmental disorders, and dementia, and brings together experts from psychiatry, computer science, and other fields to work on technologies and their implementation.
Chris Hollis - Big Data in Mental Health - 23rd July 2014 - 2
MindTech is an organization that can offer various services related to mental health technologies, including clinical and user perspectives, research expertise, governance and funding advice, and access to the NHS. They have expertise in areas like facial analysis, ambient patient monitoring, app development, serious games, and more. Their research approach involves identifying clinical problems, developing technological solutions, evaluating clinical and cost effectiveness, and disseminating solutions in the NHS. They collaborate with various partners like academics, SMEs, NHS trusts, and patients. They are working on projects involving technologies like e-mental health apps, online therapy, ambient monitoring, neuromodulation, serious games, and more to address issues like treatment adherence, assessment/diagnosis,
Will Spooner - Big Data in Mental Health - 23rd July 2014
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Chris Hollis - Big Data in Mental Health - 23rd July 2014 - 1
MindTech is a NIHR Healthcare Technology Co-operative focused on accelerating the development and adoption of innovative mental healthcare technologies. It aims to transform service delivery, enhance the patient experience, and improve outcomes through needs-led technology development with partners like patients, industry, and researchers. MindTech focuses on clinical areas like mood disorders, neurodevelopmental disorders, and dementia, and brings together experts from psychiatry, computer science, and other fields to work on technologies and their implementation.
Chris Hollis - Big Data in Mental Health - 23rd July 2014 - 2
MindTech is an organization that can offer various services related to mental health technologies, including clinical and user perspectives, research expertise, governance and funding advice, and access to the NHS. They have expertise in areas like facial analysis, ambient patient monitoring, app development, serious games, and more. Their research approach involves identifying clinical problems, developing technological solutions, evaluating clinical and cost effectiveness, and disseminating solutions in the NHS. They collaborate with various partners like academics, SMEs, NHS trusts, and patients. They are working on projects involving technologies like e-mental health apps, online therapy, ambient monitoring, neuromodulation, serious games, and more to address issues like treatment adherence, assessment/diagnosis,
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- 2. SLAM Clinical records ~250 000 patient records 18 million free text documents Available for research via the CRIS project
- 6. Information Extraction (IE) Patient ID Diagnosis Age Address 1 Depression 31 Flat 1, XYZ road 2 Cancer 67 2 Another Lane 3 Heart Attack 58 78 A place
- 7. 42% 58% Unique Medications per Patient 69% 31% Unique Diagnosis per Patient 11% 89% Unique MMSE Scores per Patient Structured Free text
- 13. Negative symptoms of psychosis Deficits of normal emotional behaviour Social withdrawal Anhedonia (inability to experience pleasure) Poverty of speech Etc. Less treatable by medication Greater affect on quality of life
- 15. Example sentences ‘Patient X has poor eye contact’ ‘I assessed the patient on 01/03/12. I noted that eye contact was poor’ ‘Saw patient X yesterday. Eye contact was bad, even worse than before’ ‘I spoke to patient X over the telephone, and was thus unable to assess eye contact’ ‘Patient X presented with the same level of eye contact as on our last meeting’
- 16. Support Vector Machines SVM produces hyperplane to classify unseen examples
- 23. Outputs Excel/CSV Knowtator format (for Arc) Gate XML Direct to database
- 24. Psychosis Symptomatology app P R F1 Apathy 0.85 1 0.93 Blunted/Flat affect 1 0.74 0.84 Concrete thinking 0.97 0.6 0.74 Emotional withdrawal 0.78 0.76 0.77 Motivation 0.75 0.63 0.68 Poverty of speech 0.81 0.87 0.84 Rapport 0.85 1 0.91 Social withdrawal 0.9 1 Anhedonia 0.96 0.83 0.89 Associations 1 0.87 0.94 Circumstantial 0.9 1 0.94 Coherence 0.85 0.98 0.91 Delusions 0.91 1 0.95 Derailment 0.91 0.96 0.94 Flight of ideas 0.93 0.97 0.94 Hallucinations 0.85 0.98 0.91 Incoherence 0.82 0.99 0.9 Poverty of thought 0.92 0.96 0.94 Tangential 0.92 1 0.95
- 26. Conclusion User friendly concept extraction Open Source Designed for simple concepts ○ > 90% P ○ > 80% R
- 27. CRIS team Rob Stewart, Matthew Broadbent, Mike Denis Chin-Kuo Chang, Richard Hayes, Alex Tulloch, Max Henderson, Gayan Perera Felicity Callard (Oversight Committee) Andrea Fernandes (Administrator) Ryan Little (data linkage) Hitesh Shetty (data extraction) Michael Ball (NLP specialist)
- 28. Sheffield team Angus Roberts Genevieve Gorrell Ian Roberts Adam Funk Mark Greenwood