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DTSTART;VALUE=DATE:20250109
DTEND;VALUE=DATE:20250111
DTSTAMP:20260826T222137
CREATED:20241020T121736Z
LAST-MODIFIED:20250312T131854Z
UID:4393-1736380800-1736553599@dsks.dk
SUMMARY:Årsmøde 2025 - Kvalitet i lyset af tidens megatrends: Strukturreform\, prioritering og afbureaukratisering
DESCRIPTION:DSKS-årsmødet afholdes 9.-10. januar 2025. \nLæs alt om program og begiveheden via link.
URL:https://dsks.dk/begivenhed/aarsmoede-2025-kvalitet-i-lyset-af-tidens-megatrends-strukturreform-prioritering-og-afbureaukratisering/
LOCATION:Syddansk Universitet\, J.B. Winsløws Vej 15\, Odense
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DTSTART;TZID=UTC:20250121T090000
DTEND;TZID=UTC:20250121T170000
DTSTAMP:20260826T222137
CREATED:20250115T134708Z
LAST-MODIFIED:20250115T134708Z
UID:4611-1737450000-1737478800@dsks.dk
SUMMARY:Workshop: Health AI Systems Thinking for Equity
DESCRIPTION:Registration and participation fee:\nDue to the high demand for this workshop\, we have introduced an application process to ensure a balanced and diverse representation of professional backgrounds and interests.\nParticipation fee: 50 DKK (no-show: 500 DKK) \nTo apply for a ticket\, please complete the participation application form via this Google Forms link. You will be notified of your application status within one week of submission. If your application is approved\, you will receive a link to purchase your ticket at 50 DKK. Please note\, a no-show fee of 500 DKK will apply to ensure commitment. We encourage you to apply as soon as possible\, as seats will be allocated on a rolling basis\, and we anticipate reaching capacity quickly.  Eligible applicants whose applications arrive after all seats have been filled will be placed on a waiting list and contacted if a spot becomes available. \nLink til tilmelding via IDA \n\nWorkshop Programme:  \nArtificial intelligence (AI) has the potential to transform healthcare worldwide. bearing promises of increased accuracy\, efficiency\, and cost-effectiveness\, in areas as diverse as drug discovery\, clinical diagnosis\, and disease management. \nFurthermore\, AI has been promoted as a tool that could expand the reach of quality healthcare to traditionally underserved patients and regions. But even with appropriate representation of marginalized communities with high-quality data\, the social patterning of the data generation process can still produce AI that is bound to preserve and even scale existing disparities in care with resulting inequities in patient outcomes. \nCreating algorithms from the digital exhaust of flawed human systems by AI developers who are not cognizant of the backstory of the data\, risks cementing inequities as permanent fixtures in healthcare delivery systems. This course will introduce students to a portfolio of methodologies that learn patterns from the data. More importantly\, it will explore data issues that if not addressed will have profound consequences on downstream prediction\, classification\, and optimization tasks. \nLearning Objectives / Key Takeaways  \nUpon successful completion of this course\, you should be able to: \n\nWork with data scientists\, social scientists\, and clinicians across the life cycle of health AI and apply systems thinking to the application of AI to healthcare\nLearn good code documentation for reproducibility of AI development\nDevelop a critical understanding of how the dataset came about from collection to aggregation to standardization\nPerform exploratory data analysis with a special emphasis on data bias\nUnderstand the basic principles of different machine learning methodologies\nInterpret and communicate analysis results\nThink about potential downstream harm from algorithm implementation\n\nWho should participate:\nStudents\, scientists\, and analysts engaged in development\, deployment or assessment and analysis of AI in healthcare and open to cross-disciplinary collaboration. \nSpeakers: \nSpeakers \n\nLeo Anthony Celi Associate Professor at Harvard Medical School\, and Clinical Research Director of the Laboratory of Computational Physiology at the MIT\nMartin Sillesen Clinical Research Lecturer in Surgery\, Rigshospitalet. Brings clinical insights into health technology research\, with a special interest in the applications of AI in surgical practices.\nAnna Schneider-Kamp Qualitative Health Researcher\, Associate Professor\, Department of Business and Management\, University of Southern Denmark\nSpecializes in qualitative health research\, with a focus on the intersection of health\, business\, and management practices.\nMatilda Dorotic Associate Professor\, Department of Marketing\, BI Norwegian Business School\, Norway. Expert in incentive structures and marketing strategies in healthcare\, studying how market mechanisms influence patient and provider behavior.\nEricka Johnson Professor\, echnology and Social Change\, Linköping University\nFocuses on the social impacts of technology\, including ethical frameworks and social challenges associated with health AI.\nMads Bundgaard Nørløv MSc BME student\, Johns Hopkins Center for Bioengineering Innovation and Design & Founder/Chair\, Copenhagen MedTech Innovator in bioengineering with expertise in medtech entrepreneurship\, fostering cross-disciplinary collaborations in health technology.\nJoão Matos PhD Student\, University of Oxford Researching applications of AI in healthcare with a focus on ethical considerations in patient data management.\nDavid Restrepo PhD Student\, Applied Mathematics\, CentraleSupélec\, University Paris-Saclay. Specialist in mathematical modeling for healthcare\, exploring new applications of AI in medical diagnostics.\nChris Sauer MD\, MPH\, PhD\, Physician\, Universitätsmedizin Essen\, and MIT Researcher Medical professional and researcher focused on integrating AI with medical practice to improve patient outcomes.\nNikolaj Munch Andersen Senior Tech Advisor\, Danish Ministry of Foreign Affairs (Udenrigsministeriet) Advisor on technology policy with a focus on AI regulations and international tech governance.\n\nProgram Committee: \n\nHenning Boje Andersen\nProfessor Emeritus\, Technical University of Denmark. Department of Technology\, Management\, and Economics / IDA Risk / DSKS Forskning.\nMartin Sillesen\nClinical Research Lecturer in Surgery\, Rigshospitalet.\nJonathan Patscheider\nVice President\, Trust Stamp\nLasse Hyldig Hansen\nBehavioural Adviser\, Danish Competition and Consumer Authority & Research Assistant\, Aarhus University\n\n\nAgenda \n\n\n\n08:30 – 09:00\nRegistration and Breakfast\n\n\n09:00 – 09:30\nWelcome and Opening Remarks\nSpeakers: Leo Anthony Celi\, Martin Sillesen\, and Henning Boje Andersen\n\n\n09:30 – 10:15\nPanel Discussion: “Beyond the Bottom Line: Which Capitals Drive Health AI?”\nPanelists: Anna Schneider-Kamp\, Martin Sillesen\nExploring the allocation of economic and sociocultural resources in health AI and how it impacts inclusivity and equity in various healthcare settings.\n\n\n10:15 – 10:25\nCoffee Break\n\n\n10:25 – 11:10\nPanel Discussion: “Reimagining Incentive Structures to Safe-Proof Health AI”\nPanelists: Matilda Dorotic\, Mads Nielsen\nA critical discussion on how incentives can be structured to prioritize patient safety and align AI advancements with healthcare goals.\n\n\n11:15 – 12:00\nPanel Discussion: “Critical Thinking as a Requisite for AI Education”\nPanelists: Ericka Johnson\, Niels Hansen\nAddressing the need for robust critical thinking in AI education and its role in developing ethical and responsible AI professionals.\n\n\n12:00 – 13:00\nLunch Break\n\n\n13:00 – 14:30\nWorkshops in parallel – Session 1  \n\nIntroduction to Machine Learning\nBias-athon\nLanguage Model Prompt-athon\nPolicy Workshop\n\n\n\n\n14:30 – 15:00\nCoffee / cake / refreshments\n\n\n15:00 – 16:30\nWorkshops in parallel – Session 2 (repeat)\n\n\n16:30 – 17:00\nSumming up\, learnings and perspectives (moderation by Leo Anthony Celi\, Martin Sillesen)\n\n\n\n  \n\nWorkshop teasers \nIntroduction to Machine Learning \nThis is a primer on machine learning concepts including but not limited to cross-validation\, data leakage\, benchmarks\, performance metrics\, and fairness evaluation. Publicly available high-resolution datasets (not registries) will be introduced: MIMIC (US)\, eICU-CRD (US)\, AmsterdamUMCdb (Netherlands)\, HiRID (Switzerland)\, SICdb (Austria). \nBias-athon \nThe Bias-athon is designed to address and mitigate biases in artificial intelligence (AI) systems. This workshop will leverage interdisciplinarity to identify\, understand\, and develop strategies to understand biases in clinical AI datasets. Participants will engage in hands-on sessions where they explore various types of biases\, such as measurement bias\, and variation in the degree of monitoring from social determinants of care\, and their impact on AI performance. \nLanguage Model Prompt-athon \nA prompt-athon is focused on enhancing effectiveness and reducing the bias of large language models. This workshop is designed for clinicians who are already or who are thinking of using these tools for summarizing patient courses\, drafting content for progress notes and letters to other providers and patients\, and soliciting differential diagnoses\, treatment recommendations\, and prognostication. Participants will be introduced to various prompt engineering techniques that can leverage the power of this technology. Through collaborative exercises\, attendees will experiment with different types of prompts\, analyze the outputs\, and refine their strategies to achieve better results. The event will also include discussions on the challenges of prompt design\, such as avoiding ambiguity and ensuring context-appropriateness. \nPolicy Workshop \nThe Policy Workshop is organized to explore the regulatory and ethical frameworks surrounding the use of AI technologies. Sessions will cover a range of topics\, including transparency and accountability\, power structures\, and the political economy that drives the impact of AI. Participants will engage in brainstorming and dialogue and propose solutions to complex policy issues. The goal is to engender a systems-thinking mindset among developers and users of AI to improve population health. \n\nQUESTIONS THAT PARTICIPANTS MUST ANSWER IN ORDER TO COMPLETE SIGN-UP \n\nDescribe your current role and how it relates to the development\, deployment\, and/or evaluation and analysis of AI technologies in healthcare. Include any specific projects or study programmes and your involvement.\nWhat do you hope to gain from participating in this workshop\, and how do you anticipate applying the insights to your work or studies?\n\n\nOrganizers:\nIDA Risk – IDA Engineering Society; MIT/Massachusets Institute of Technology; DSKS – Dansk Selskab for Kvalitet i Sundhedssektoren; Rigshospitalet/ Københavns Universitet; DTU Health Tech;  Copenhagen Medtech.    \nSponsor \nThe workshop is sponsored by DDSA – Danish Data Science Academy
URL:https://dsks.dk/begivenhed/workshop-health-ai-systems-thinking-for-equity/
LOCATION:IDA Conference\, København V\, Kalvebod Brygge 31-33\, København
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DTSTART;TZID=UTC:20250127T170000
DTEND;TZID=UTC:20250127T200000
DTSTAMP:20260826T222137
CREATED:20250115T134952Z
LAST-MODIFIED:20250123T231301Z
UID:4613-1737997200-1738008000@dsks.dk
SUMMARY:Sikkerhedsstyring med fokus på hvad der lykkes: Erfaringer fra offshore\, luftfart og sundhedsvæsen
DESCRIPTION:Tilmelding: \n\n\n\nFysisk arrangement i IDA Mødecenter. Medlemmer af arrangørers organisationer har gratis adgang til fysisk deltagelse ved arrangementet. For andre: 200 DKK: Link til tilmelding \nSimTrans-medlem og DSKS-medlem: Vælg for din profil ”ansættelsessted” firma nr. 2300650 (SimTrans) eller søg ”Det danske selskab for simulatortræning\, menneske…”; eller firma nr. 2297633 (DSKS) eller søg ”Dansk Selskab for Kvalitet i Sundhedssektoren”: Tilmelding til online deltagelse \n\n\n\n\nProgram \nTraditionel sikkerhedsstyring har været fokuseret på hvad der mislykkes. Nyere tilgange lægger vægt på at forstå og lære af vellykket håndtering af såvel rutineprægede som kritiske situationer. Hør eksperters erfaring fra flere sektorer. \nProgram \n\n\n\n17:00\nIntroduction and welcome \n\n\n\nIndledning og velkomst v/ Henning Boje Andersen (IDA Risk/ DSKS /SimTrans) \n\n\n\n\n\n\n17:10\n\n\n\n\nFra ”læring af fejl” til ”læring af succes”. v/ Thomas Koester \n\n\n\nv/ Thomas Koester\n\n\n18:00\n\n\n\n\nSandwich\, drikkevarer og netværk \n\n\n\n\n\n\n18:20\n\n\n\n\nErfaringer fra luftfart med Safety II. \nv/ Tom Laursen \n\n\n\n\n\n\n19:00\n\n\n\n\nAnvendelse af Safety II og FRAM i sundhedsvæsenet.  \nv/ Bettina Ravnborg Thude og Frans Brandt Kristensen \n\n\n\n\n\n\n19:40\n\n\n\n\nDebat og spørgsmål og svar \n\n\n\n\n\n\n20:00\n\n\n\n\nTak for i dag \n\n\n\n\n\n\n\n\n\n\nThomas Koester er cand.psych og specialist i human factors med udstrakt erfaring (+20 år) fra forskellige industrier: Maritim transport\, olie & gas\, jernbaner\, hospitaler\, vejtrafik\, byggeri og infrastruktur\, kontrolrum\, produktudvikling og design\, medicinsk udstyr m.m. Thomas har skrevet flere bøger\, bl.a. ”Human Factors in the Maritime Domain” og ”Terminology Work in Maritime Human Factors” \n\n\n\nTom Laursen er flyveleder og træningsspecialist hos GATE Aviation Training. Tom har samtidig med sit virke som flyveleder over 20 års erfaring med human factors og sikkerhedsarbejde. Han har en MA fra Linköpings Universitet i menneskelige faktorer og systemsk sikkerhed og kombinerer sin teoretiske viden med praktisk erfaring inden for luftfart. \n\n\n\nBettina Ravnborg Thude\, PhD er forsker og chefkonsulent i Medicinske Sygdomme\, Sygehus Sønderjylland\, Region Syddanmark. \n\n\n\n\n\n\nFrans Brandt Kristensen MPM\, PhD\, er cheflæge og forskningsleder i Medicinske Sygdomme\, Sygehus Sønderjylland\, Region Syddanmark\, og klinisk lektor. \n\n\n\n\n\n\nBettina og Frans har udstrakt erfaring med sikkerhedsstyring i sundhedsvæsenet\, herunder med anvendelse af FRAM og RAG analyserne til fremme af patientsikkerhed og optimering af driften. \n\n\n\n\nIntroduktion \n\n\n\nTraditionelle tilgange til risikostyring i sikkerhedskritiske sektorer som luftfart\, offshore\, søfart og sundhedssektoren har vist sig at være utilstrækkelige. Fokus har primært været på at etablere præventive barrierer og arbejdsprocedurer samt at drage læring fra ulykker og nærved-hændelser. \nDisse tilgange bygger på en vis grad af overmod – idéen om\, at enhver måde\, hvorpå tingene kan gå galt\, kan forudses\, og at undersøgelser af fejl og ulykker er den centrale kilde til at forbedre sikkerheden. Som en væsentlig korrektion og supplement til denne tilgang (Safety I) er der i de senere år udviklet metoder\, der fokuserer på det\, der går godt i det daglige arbejde (Safety II). Med andre ord\, man kan ikke lære at udføre sikkerhedskritiske og komplekse opgaver\, hvis man udelukkende fokuserer på fejl og hvad der mislykkes; man må undersøge den variationen i hvordan operatører lykkes under både normale og kritiske situtioner. \nPå seminaret beretter eksperter fra luftfart\, offshore/søfart og sundhedssektoren om erfaringer med Safety II-inspirerede tilgange\, og der vil være god lejlighed til at sammenligne på tværs af sektorer og stille spørgsmål. \nArrangementet er arrangeret af IDA Risk i samarbejde med Dansk Selskab for Kvalitet i Sundhedssektoren (DSKS) og SimTrans. Medlemmer af arrangører har gratis adgang. Andre: 200 kr.
URL:https://dsks.dk/begivenhed/sikkerhedsstyring-med-fokus-paa-hvad-der-lykkes-erfaringer-fra-offshore-luftfart-og-sundhedsvaesen/
LOCATION:IDA Conference\, København V\, Kalvebod Brygge 31-33\, København
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