Data Science Summary -- 2

Need 10 summaries for the following 10 videos on data science. Word limit 80-100 words per summary. Just write one or two paragraph at max per summary.

1) What is a Stepped-Wedge Trial? What is a Stepped-Wedge Trial?

Clinical trials are at the core of our clinical science. But how to we design a clinical experiment? When do we deviate from the “gold standard” of a randomized control trial? Mona and Ada discuss the stepped-wedge trial design and recent work in the field.

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2) Needs-led Innovation at Oxford University Needs-led Innovation at Oxford University

Originally developed in the Stanford biodesign ecosystem, the “needs-led” approach to healthtech innovation has rapidly become a key philosophy for those wanting to develop a viable healthcare solution. Prof. Jeroen Bergmann and Daniel Mogefors from the Oxford Healthtech Labs break down the key aspects of needs-led innovation and how researchers at Oxford University are using it.

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3) Berg Health's Data Platforms and Pharmaceutical Innovation Berg Health's Data Platforms and Pharmaceutical Innovation.

Niven Narain, CEO of Berg Health, discusses creating value through data platforms and AI in the pharmaceutical industry.

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4) Ufonia's Automated Patient Phone Screening Ufonia's Automated Patient Phone Screening

Neurosurgeon and entrepreneur Nick de Pennington talks about the importance of automating clinical tasks to help doctors focus on the most challenging cases.

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5) Leveraging Data for Clinical Development & the OC Biostatistics Symposium Leveraging Data for Clinical Development & the OC Biostatistics Symposium

Gajanan Bhat and Xinping Cui discuss the major themes of data science in clinical drug and device development.

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6) What are a Clinician's Priorities for Data-Driven Medicine?

Rob Scott, Chief Medical Officer at AbbVie, discusses the importance of a clinician’s perspective for keeping clinical trial development focused on the patients. He then covers the key areas in which new developments in healthcare technology and patient-specific data can help us better understand a patient’s response to therapies and interventions.

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7) Data Platforms to Monitor Animal Health Data Platforms to Monitor Animal Health.

The episode of milk and honey. Shane shows us some of the real-time data analytics platforms that track the health of dairy cows and honey bees. From wearables to stationary sensors, animals’ health is being monitored via rich multivariate time series, which leads to plenty of opportunities for analysis and optimization. Shane highlights how these machine learning applications have a great benefit to the animals health along with a strong business case. It’s a great visual presentation, where Shane shows you the data behind animal health decision making.

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8) Virtual and Augmented Reality in the Life Sciences - I.

Mike McArdle, co-founder and Chief Product Officer at Lucid Dream VR, breaks down the key technological factors that have led to the rapid increase in VR and AR solutions for the life sciences. He then walks us through two products helping companies and hospitals to accelerate training and talent development on their staff.

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9) Virtual and Augmented Reality in the Life Sciences - II .

Mike is back to walk us through applications of VR that helps clinicians train for rare events and better understand the patient’s experience.

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10) Engineering Sensing Platforms for Biomarker Detection Engineering Sensing Platforms for Biomarker Detection

Dana al Sulaimen’s (MIT) gives a great presentation on the clinical motiv

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Taidot: Tilastotiede, Tutkimusten kirjoitus, Tilastoanalyysi, Datatiede, LESS/Sass/SCSS

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