• Launch Event (Passcode: 212278) VU Campus Center for AI & Health

    The Vrije Universiteit (VU) Amsterdam, Amsterdam UMC - location VUmc and ACTA are setting up the VU Campus Center for AI & Health. The purpose of the Center is both to fuel collaborations on and outside the VU campus and to increase the visibility of the research in the AI & Health area with the ultimate goal to improve healthcare by developing, implementing and evaluating AI technologies. Across Amsterdam the center is connected to other partners (such as the UvA, CWI, etc.) through collaboration platforms such as Amsterdam Medical Data Science and Smart Health Amsterdam and the overarching collaboration in the Amsterdam AI Coalition themed โ€œAI:Technology for Peopleโ€. To celebrate the launch of this Center, a launch event is organized with presentations of researchers in the area of AI & Health. This event is open to all with an interest in AI & Health. Please find an outline of the program below: ===================================================================== Welcome + purpose of the center (Heleen Riper (VU Psychology), Mark Hoogendoorn (VU Computer Science), Marleen Huysman (VU School of Business and Economics), and Robert de Jonge (Amsterdam UMC, Clinical Chemistry)) ===================================================================== Opening center (Chris Polman (Executive Board Amsterdam UMC) and Mirjam van Praag (Executive Board VU)) ===================================================================== Keynote talk: AutoML and interpretability: powering the machine learning revolution in healthcare (Mihaela van der Schaar, University of Cambridge) Abstract: AutoML and interpretability are both fundamental to the successful uptake of machine learning by non-expert end users. The former will lower barriers to entry and unlock potent new capabilities that are out of reach when working with ad-hoc models, while the latter will ensure that outputs are transparent, trustworthy, and meaningful. In healthcare, AutoML and interpretability are already beginning to empower the clinical community by enabling the crafting of actionable analytics that can inform and improve decision-making by clinicians, administrators, researchers, policymakers, and beyond. This keynote presents state-of-the-art AutoML and interpretability methods for healthcare developed in our lab and how they have been applied in various clinical settings (including cancer, cardiovascular disease, cystic fibrosis, and recently Covid-19), and then explains how these approaches form part of a broader vision for the future of machine learning in healthcare. See https://www.vanderschaar-lab.com/prof-mihaela-van-der-schaar/ for a bio. ===================================================================== Talks by junior researchers at the VU Campus working on AI & Health: * Improvement and evaluation of AI techniques for Personalized Mental Health Interventions - Marketa Ciharova (VU Clinical Psychology) and Ali el Hassouni (VU Computer Science) * The intersection of AI and Knowledge Work: A Case Study in Radiology - Bomi Kim (VU School of Business and Economics) * Deep Learning for Tumor Response Evaluation - Nina Wesdorp (Amsterdam UMC - Cancer Center Amsterdam) ===================================================================== The session will take place online via Zoom. The link will be shared to those who registered for the event. The password to enter is[masked]

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  • ADS & AMDS Webinar | ๐—ง๐—ฒ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ: ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต

    Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿณ: ๐—ง๐—ฒ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ผ๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐—ฑ๐˜‚๐—ฟ๐—ถ๐—ป๐—ด ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ฒ (TBA) What did we learn from teaching Data Science online? What are the experiences from the teachers and the students? How do you keep personal contact? How can you do group assignments? Which technology is useful, which technology is more difficult? What are the do's and donโ€™ts? ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ TBA Date: 15 or 16 July 2020 TBA Time: 12:00-13:00 Zoom details to follow soon.

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  • ADS & AMDS Webinar | COVID-19 and Public Transport Capacity Models

    Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿฑ: ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฎ๐—ป๐—ฑ ๐—ฐ๐—ฎ๐—ฝ๐—ฎ๐—ฐ๐—ถ๐˜๐˜† ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—ฝ๐˜‚๐—ฏ๐—น๐—ถ๐—ฐ ๐˜๐—ฟ๐—ฎ๐—ป๐˜€๐—ฝ๐—ผ๐—ฟ๐˜ ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ฒ 12:00 Welcome & Introduction 12:05 Talk by Dennis Huisman and Menno de Bruyn 12:40 Q&A 13:00 End! Since Mark Rutte's press conference on March 12, many people are studying and working from home. As a consequence, the number of passengers using public transport has significantly dropped. On Friday March 13, the number of passengers was 85% lower than on a regular Friday. The following week, the reduction was even larger. At the same time, the percentage of employee illness increased significantly. In this presentation, we will first talk about the short-term challenges NS faced. From March 21 to June 1, NS operated a significantly reduced timetable. We will discuss how this timetable was designed and how advanced algorithms were used to construct this timetable (and the steps to return to the normal timetable) and the related rolling stock and crew schedules. We will also talk about the challenges that NS will face in the coming years. Passenger demand will be reduced in the coming years due to the economic depression, other behaviour (working from home and online lectures) and passengers' fear of using public transport. To get better predictions on travel behaviour, NS started a large customer survey on passenger behaviour after the COVID-19 crisis. We will present the first results of this survey and the expected impact on NS. ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ Dennis Huisman is Expertise Manager Logistic Processes at NS and Endowed Professor Public Transport Optimization at Erasmus University Rotterdam Menno de Bruyn is Team Lead Transportation Research at NS Date: Thursday 2 July 2020 Time: 12:00-13:00

  • ADS & AMDS Webinar | ๐—ฃ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐—ฐ๐˜† ๐—ฑ๐˜‚๐—ฟ๐—ถ๐—ป๐—ด ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต

    Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿฎ: ๐—ง๐—ต๐—ฒ ๐—ฑ๐—ฒ๐—น๐—ถ๐—ฐ๐—ฎ๐˜๐—ฒ ๐—ฏ๐—ฎ๐—น๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—ฏ๐—ฒ๐˜๐˜„๐—ฒ๐—ฒ๐—ป ๐—ฃ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐—ฐ๐˜† ๐—ฎ๐—ป๐—ฑ ๐—›๐—ฒ๐—ฎ๐—น๐˜๐—ต ๐—ฑ๐˜‚๐—ฟ๐—ถ๐—ป๐—ด ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ฒ 12:00 Welcome & Introduction 12:05 Talk by Hester de Vries (Kennedy Van der Laan) 12:40 Q&A 13:00 End! It is a very delicate ethical question that appears with the COVID-19 App: on the one hand the Health of the population which is at stake, on the other hand the Privacy of the individual. Apart from this ethical question, there is also a relevant technical question: could Health Apps really help to reduce the transmission of COVID-19? Or is this an idea that has never been proven? ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ Hester de Vries, Attorney at Law (Kennedy Van der Laan) Title: GDPR & COVID-19 Pandemic The COVID-19 pandemic is an exceptional and developing situation. Organizations feel the need to immediately take precautionary measures to prevent or limit the (further) spread of the virus where possible. Crisis situations for their organization must be averted from a human, functional and financial standpoint. The precautionary measures often result in some kind of processing personal data. Concerns are growing about the intensity and spread of monitoring techniques in order to try and keep control of the virus. Will China become our foreland in respect of surveillance as well? In order for an organization to legitimately process personal data, and in particular: health data, the (strict) rules of GDPR and the applicable local implementation acts need to be complied with. In this webinar, Hester de Vries will focus on some typical questions regarding the legitimacy of temperature measuring at the workplace and some new forms of monitoring techniques developed in the course of the COVID-19 Pandemic, including proximity notification apps. Date: 1 July 2020 Time: 12:00-13:00

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  • ADS & AMDS Webinar | Modelling effects of COVID-19 policy measures

    Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿฐ: ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ฒ๐—ฐ๐—ผ๐—ป๐—ผ๐—บ๐—ถ๐—ฐ ๐—ฎ๐—ป๐—ฑ ๐—ต๐—ฒ๐—ฎ๐—น๐˜๐—ต ๐—ฒ๐—ณ๐—ณ๐—ฒ๐—ฐ๐˜๐˜€ ๐—ผ๐—ณ ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฝ๐—ผ๐—น๐—ถ๐—ฐ๐˜† ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ฒ 16:00 Welcome & Introduction 16:05 Talk by Kent Smetters, Alex Arnon and John Ricco 16:40 Q&A 17:00 End! This presentation will be about a model that has been developed at Wharton to simulate the economic and health effects of policy decisions. For a detailed model description: https://budgetmodel.wharton.upenn.edu/issues/2020/5/1/coronavirus-reopening-simulator ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ Kent Smetters is the Boettner Chair Professor at the University of Pennsylvaniaโ€™s Wharton School and a Faculty Research Fellow at the National Bureau of Economic Research. Alex Arnon is Senior Analyst at the Penn-Wharton Budget Model John Ricco is Senior Analyst at the Penn-Wharton Budget Model Date: Wednesday 24 June 2020 Time: 16:00-17:00 Zoom link is available for registered participants.

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  • ADS & AMDS Webinar | Predictive Modelling for COVID-19 Patients in Hospitals

    ** special announcement: 2. job openings. https://www.linkedin.com/pulse/data-against-corona-we-hiring-paul-elbers-md-phd-edic/ ** Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿฏ: ๐—ฃ๐—ฟ๐—ฒ๐—ฑ๐—ถ๐—ฐ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ณ๐—ผ๐—ฟ ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฝ๐—ฎ๐˜๐—ถ๐—ฒ๐—ป๐˜๐˜€ ๐—ถ๐—ป ๐—ต๐—ผ๐˜€๐—ฝ๐—ถ๐˜๐—ฎ๐—น๐˜€ ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Host: Lucas Fleuren (Amsterdam UMC/AMDS/VU), Marc Salomon (ABS UvA, ADS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ Daan de Bruin (PacMed) and Bjorn van der Ster (Amsterdam UMC) Daan de Bruin (PacMed) Title: Building a national COVID-19 ICU database: challenges, solutions and opportunities In collaboration with the NVIC, NICE and the Amsterdam UMC, Pacmed takes part in a consortium to gather insights to improve treatment strategy of COVID-19 patients in the intensive care unit (ICU). Since the COVID-19 patient data of a single ICU is insufficient to generate meaningful insights, Dutch ICUs have joined forces and share data with each other. Over thirty ICUs are already participating. The task of standardising this data to a common data format is enormous. Not only because of data volumes, but also because of data heterogeneity: ICUs register thousands of different vital signs, lab parameters and medications, however they all use their own parameter naming and unit conventions. This talk will highlight: 1. The challenges of dealing with large data sets of such a huge number of different medical institutions 2. The infrastructure built to combine and standardise the various data sources 3. The opportunities for improving COVID treatment originating from ICUs joining forces Bjorn van der Ster (Amsterdam UMC) Title: Visualising and predicting a new disease in the community; a case of reusing public data and COVID-19 Prior to the occurrence of the first COVID-19 cases in the Netherlands, the DYNAMO research group at Amsterdam UMC, location AMC had been working on developing machine-learning models to predict acute disease presentations to the emergency room at a regional level for non-infectious (like stroke, hart attacks, trauma) and infectious disease (pneumonia, influenza). The aim is to make acute care needs more predictable to improve planning, optimise resource allocation, and improve patient and hospital staff experience. We had just build a well-performing model to predict influenza outbreaks and peak admissions at a local level. Nivel, RIVM, KNMI and CBS are our partners in this project. As COVID-19 started to impact all of us, we decided to focus on mere re-presentation of available public data in a more visual way and focus on local trends. The first version of this first efforts can now be found on www.windfall.ai Second, we started using different approaches to predict new COVID-19 cases, hospital admissions and deaths for the coming four days. Currently, we are trying to use more public data (traffic, socio-economic,โ€ฆ) to improve the performance of the models and the outlook. Moreover, we are talking to Maltese and UK governments as they are now also looking at using a similar approach. Anyone can receive the data from us that we use and get the models. Date: 24 June 2020 Time: 12:00-13:00 Zoom details are available once registered.

  • ADS & AMDS Webinar | Different Scenarios for Exit Strategies in COVID-19

    Amsterdam Data Science (ADS) and Amsterdam Medical Data Science (AMDS) are co-hosting a new lecture series in collaboration with Elsevier and Google to explore ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฎ๐—ป๐—ฑ ๐—ช๐—ฒ๐—ฎ๐—ธ๐—ป๐—ฒ๐˜€๐˜€ ๐—ผ๐—ณ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—น๐—ถ๐—ป๐—ด ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต. Aims: - Showcase the power and limitations of data centred approaches - Jointly understand and learn from the different COVID approaches and views - Shape the time for Data Science research/education after the lock-down ๐—Ÿ๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐Ÿญ: ๐——๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜ ๐˜€๐—ฐ๐—ฒ๐—ป๐—ฎ๐—ฟ๐—ถ๐—ผ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ฒ๐˜…๐—ถ๐˜ ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ฒ๐—ด๐—ถ๐—ฒ๐˜€ ๐—ถ๐—ป ๐—–๐—ข๐—ฉ๐—œ๐——-๐Ÿญ๐Ÿต ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐—บ๐—ฒ 12:00 Welcome & Introduction 12:05 Talk #1: Bert Slagter + Q&A 12:30 Talk #2: Edwin van den Heuvel + Q&A 12:55 Panel discussion 13:15 End! ๐— ๐—ผ๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS) ๐—ฆ๐—ฝ๐—ฒ๐—ฎ๐—ธ๐—ฒ๐—ฟ๐˜€ ๐—•๐—ฒ๐—ฟ๐˜ ๐—ฆ๐—น๐—ฎ๐—ด๐˜๐—ฒ๐—ฟ (founder Procurios) The COVID-19 pandemic is a complex system with many unknowns and uncertainties. There is data, but is it reliable? And how do we make decisions when data (and evidence) is incomplete or contradictory? We'll visit three phases of the pandemic from this perspective: 1) Estimating required ICU capacity in the early stages of lockdown 2) Constructing a reliable exit plan 3) Building a dashboard that minimizes the risk of a second wave ๐—˜๐—ฑ๐˜„๐—ถ๐—ป ๐˜ƒ๐—ฎ๐—ป ๐—ฑ๐—ฒ๐—ป ๐—›๐—ฒ๐˜‚๐˜ƒ๐—ฒ๐—น (professor in statistics TU Eindhoven) Title: Predictions and changes in spread of the corona virus in different countries โ€“ data-oriented approaches During the beginning of the COVID-19 crisis in the Netherlands, we started to monitor and predict the number of infections and deaths in the short-term and long-term in several countries. Our analysis are based on the official reported numbers from governmental institutes, knowing that this type of data could be non-representative for the population of a country. Therefore, we used different logistic growth curves and epidemic disease models to obtain a better understanding of the daily information and temporal changes present in the data. Based on our data-oriented approaches we tried to determine as soon as possible when countries reached their turning point in virus spread and we tried to help determine the required hospital intensive care capacity with our predictions. Furthermore, we could identify which governmental measures had an impact on the โ€œeffective contact rateโ€ within a country. Date: Thursday 11 June 2020 Time: 12:00-13:15 https://us02web.zoom.us/j/83197431349

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  • 15th Medical Data plus Pizza meeting

    Amsterdam UMC - location VUmc - ICU - Room Delta

    AMDS is growing! Join us! Everything medical data science. And pizza. This edition features: ** Phosphoproteomics for Precision Medicine - Connie Jiminez (Pulmonology, Amsterdam UMC) **Deep generative modeling for histopathology images - Jakub Tomczak (VU, Amsterdam) followed by discussion and networking with pizza.