Oplægget blev holdt ved InfinIT-arrangementet "Sammenhængende patientforløb, sundheds-processer og it" afholdt den 20. april 2012. Læs mere om arrangementet på http://www.infinit.dk/dk/hvad_kan_vi_goere_for_dig/viden/reportager/en_forandret_sundhedssektor_med_it.htm
This document discusses challenges with hardware-near programming and proposes solutions like object-oriented design, test-driven development, and mocking hardware for testing in C. It provides examples of encapsulating hardware registers in C and writing tests that check register values and function outputs without the physical hardware. The document concludes that while setting up the tools is an initial investment, TDD is possible and helps create safe, maintainable low-level software.
This document summarizes an embedded software project that used object-oriented modeling and design with UML, along with Safety-Critical Java and C programming. A team of students created a model car that could be remotely controlled via an app. The project followed an object-oriented development process, including use case modeling, component diagrams, and testing of components using mock objects. The design included a layered architecture with hardware abstraction and platform abstraction layers. Missions in Safety-Critical Java were used to model different car modes like Park and Drive. Unit testing of components and testing on the execution platform helped evaluate memory usage and schedulability. The document concludes that this approach helped manage complexity in the embedded system.
The document summarizes a company's conversion of its embedded controller software from C to C++ over a two month period. It involved converting 8 projects with 30% shared code across 18 developers. Challenges included converting callbacks and dealing with scripting errors. Opportunities included improving code quality, team building, and evaluating new static analysis tools. The conversion was successful with minimal performance impacts and many bugs were found and fixed during the process. Future plans include C++ training and refactoring code to fully utilize C++ features.
This document discusses embedded Linux development from a manager's perspective. It provides the speaker's background working with C and C++ on embedded systems. Key expectations of programming languages for embedded systems are outlined, including flexibility, low cost, and real-time performance. The document discusses why C is commonly used for embedded development and outlines best practices like code reviews when using C to avoid issues. It also discusses moving to C++ and using Linux for embedded projects.
The document discusses the C programming language. It provides some key facts about C:
- C was developed in the late 1960s and early 1970s by Dennis Ritchie at Bell Labs.
- C became popular due to its use in developing the UNIX operating system.
- The IT world widely uses C, as evidenced by its use in operating systems like Linux, Windows, and iOS.
- The C language has undergone standardization with standards published in 1989 (C89), 1999 (C99), 2011 (C11), and 2018 (C18).
- C influenced many other popular programming languages and remains one of the most widely used languages today.
The document discusses the evolution of industrial revolutions and key elements of Industry 4.0, including intelligent automation and production facilities, smart products, virtual production, and more. It also examines the increasing need for systems engineering as products and production become more complex. Finally, it outlines six key fields that must be mastered for successful digital transformation: usage, data, technology, process, role, and culture.
This document discusses challenges with hardware-near programming and proposes solutions like object-oriented design, test-driven development, and mocking hardware for testing in C. It provides examples of encapsulating hardware registers in C and writing tests that check register values and function outputs without the physical hardware. The document concludes that while setting up the tools is an initial investment, TDD is possible and helps create safe, maintainable low-level software.
This document summarizes an embedded software project that used object-oriented modeling and design with UML, along with Safety-Critical Java and C programming. A team of students created a model car that could be remotely controlled via an app. The project followed an object-oriented development process, including use case modeling, component diagrams, and testing of components using mock objects. The design included a layered architecture with hardware abstraction and platform abstraction layers. Missions in Safety-Critical Java were used to model different car modes like Park and Drive. Unit testing of components and testing on the execution platform helped evaluate memory usage and schedulability. The document concludes that this approach helped manage complexity in the embedded system.
The document summarizes a company's conversion of its embedded controller software from C to C++ over a two month period. It involved converting 8 projects with 30% shared code across 18 developers. Challenges included converting callbacks and dealing with scripting errors. Opportunities included improving code quality, team building, and evaluating new static analysis tools. The conversion was successful with minimal performance impacts and many bugs were found and fixed during the process. Future plans include C++ training and refactoring code to fully utilize C++ features.
This document discusses embedded Linux development from a manager's perspective. It provides the speaker's background working with C and C++ on embedded systems. Key expectations of programming languages for embedded systems are outlined, including flexibility, low cost, and real-time performance. The document discusses why C is commonly used for embedded development and outlines best practices like code reviews when using C to avoid issues. It also discusses moving to C++ and using Linux for embedded projects.
The document discusses the C programming language. It provides some key facts about C:
- C was developed in the late 1960s and early 1970s by Dennis Ritchie at Bell Labs.
- C became popular due to its use in developing the UNIX operating system.
- The IT world widely uses C, as evidenced by its use in operating systems like Linux, Windows, and iOS.
- The C language has undergone standardization with standards published in 1989 (C89), 1999 (C99), 2011 (C11), and 2018 (C18).
- C influenced many other popular programming languages and remains one of the most widely used languages today.
The document discusses the evolution of industrial revolutions and key elements of Industry 4.0, including intelligent automation and production facilities, smart products, virtual production, and more. It also examines the increasing need for systems engineering as products and production become more complex. Finally, it outlines six key fields that must be mastered for successful digital transformation: usage, data, technology, process, role, and culture.
Emergent synthetic processes (ESP) is a new paradigm for implementing process changes without needing agreement from all participants. It works by having organizational members define service descriptions stating what tasks they are willing to do and under what conditions. Processes are then synthesized in real-time from these service descriptions for each specific case, finding the optimal route through the organization. This allows service descriptions and partially completed processes to be updated at any time without requiring agreement. ESP enables a more flexible and distributed approach to processes and workflow.
This document discusses the integration of DCR (Dynamic Case Resolution) with the KMD Workzone case management platform to enable more automated and adaptive case resolution. It envisions using technologies like machine learning, artificial intelligence, and automation to handle more routine case activities while still allowing for human judgment and deviations from standard workflows. The approach is described as evolutionary rather than revolutionary, breaking large changes into smaller, configurable steps and getting users involved to identify automatable activities and ensure the system meets their needs. Demostrations are provided of Workzone's flexible configuration capabilities and how DCR could be integrated to iteratively introduce more automated case resolution over time.
SupWiz is a spin-off from world-leading AI experts that develops omni-channel AI software to disrupt customer service and support. Their platform makes different customer service channels intelligent and links them together using techniques like intelligent virtual agents, knowledge management, and analytics. The platform integrates with infrastructure components and has been proven valuable at several customers, accurately answering questions and reducing response times. SupWiz aims to improve the customer experience throughout the entire journey with AI-powered solutions.
The document discusses NNIT's vision for its Service Support Center to improve user productivity through reducing demand for support. Key points include:
- Integrating all user interaction data across systems to create a single source of truth data warehouse for metrics and reporting.
- Implementing configuration management policies, SLA policies, and integrating different levels of knowledge and problem management to reduce support demand and minimize downtime.
- The goal is machine-learning enabled intelligent automation that is flexible, consistent and cost-efficient to provide support across channels like phone, chat, and with multi-language translation available 24/7 globally.
- Statistics are presented on ticket routing optimization using AI to reduce unnecessary ticket jumps between support agents.
This document discusses how natural language processing (NLP) can be used for customer support. It outlines several NLP applications for customer support like search, fraud detection, and translation. It also discusses how NLP can help answer previously unasked questions by generating questions from knowledge bases and documents. Finally, it proposes a "customer support Turing test" to evaluate NLP systems for their ability to fool classifiers that distinguish customer support agents from customers.
This document provides information about an AI conference on the future of customer service. The conference will feature presentations from leaders in various AI and data organizations, as well as a panel debate. Statistics are presented showing the growing importance and impact of AI and chatbots on customer service interactions and cost savings over the coming years. The AMAOS project from the University of Copenhagen is also introduced, which focuses on advanced machine learning for automated omni-channel customer support.
The document discusses a project aimed at improving quality of life for citizens with affective disorders like depression. It outlines a vision called "Psyche" that aims to anticipate and alleviate acute depression through a digital platform. A configuration table presents the rationale, strategy, and tactics for a prospect to realize this vision, including leveraging the user's digital diary and questionnaire responses to detect emerging depressive episodes and provide alleviation measures. The table identifies challenges like ineffective intervention and underused platform potential, noting that anticipation works but could be improved and alleviation measures are sometimes weak or misplaced.
This document discusses spasticity management and Inerventions' product called Mollii, which uses electrical therapy to reduce spasticity and improve motor control for people with conditions like cerebral palsy, stroke, and multiple sclerosis. Mollii is a medical device suit with electrodes that can be individually programmed. Clinical studies in Sweden and Denmark show that Mollii reduces spasticity and facilitates voluntary movement, helping users to live more freely. Inerventions' vision is for Mollii to become a natural first choice for non-invasive spasticity management.
This document discusses several robots that can be used in healthcare settings including Giraff, Toyota Human Support Robot, and OriHime. It also mentions technologies such as the R3 platform, robot control by gaze from bed, and positioning with roof fiducials. The document appears to cover different robots available for healthcare as well as some of their capabilities and technologies involved in their operation.
This document discusses unit testing and code coverage measurement in the software development process. It describes refactoring code to enable unit testing by adding assert macros and a test program. The document also mentions measuring test coverage to ensure code is thoroughly tested during the refactoring process.
Emergent synthetic processes (ESP) is a new paradigm for implementing process changes without needing agreement from all participants. It works by having organizational members define service descriptions stating what tasks they are willing to do and under what conditions. Processes are then synthesized in real-time from these service descriptions for each specific case, finding the optimal route through the organization. This allows service descriptions and partially completed processes to be updated at any time without requiring agreement. ESP enables a more flexible and distributed approach to processes and workflow.
This document discusses the integration of DCR (Dynamic Case Resolution) with the KMD Workzone case management platform to enable more automated and adaptive case resolution. It envisions using technologies like machine learning, artificial intelligence, and automation to handle more routine case activities while still allowing for human judgment and deviations from standard workflows. The approach is described as evolutionary rather than revolutionary, breaking large changes into smaller, configurable steps and getting users involved to identify automatable activities and ensure the system meets their needs. Demostrations are provided of Workzone's flexible configuration capabilities and how DCR could be integrated to iteratively introduce more automated case resolution over time.
SupWiz is a spin-off from world-leading AI experts that develops omni-channel AI software to disrupt customer service and support. Their platform makes different customer service channels intelligent and links them together using techniques like intelligent virtual agents, knowledge management, and analytics. The platform integrates with infrastructure components and has been proven valuable at several customers, accurately answering questions and reducing response times. SupWiz aims to improve the customer experience throughout the entire journey with AI-powered solutions.
The document discusses NNIT's vision for its Service Support Center to improve user productivity through reducing demand for support. Key points include:
- Integrating all user interaction data across systems to create a single source of truth data warehouse for metrics and reporting.
- Implementing configuration management policies, SLA policies, and integrating different levels of knowledge and problem management to reduce support demand and minimize downtime.
- The goal is machine-learning enabled intelligent automation that is flexible, consistent and cost-efficient to provide support across channels like phone, chat, and with multi-language translation available 24/7 globally.
- Statistics are presented on ticket routing optimization using AI to reduce unnecessary ticket jumps between support agents.
This document discusses how natural language processing (NLP) can be used for customer support. It outlines several NLP applications for customer support like search, fraud detection, and translation. It also discusses how NLP can help answer previously unasked questions by generating questions from knowledge bases and documents. Finally, it proposes a "customer support Turing test" to evaluate NLP systems for their ability to fool classifiers that distinguish customer support agents from customers.
This document provides information about an AI conference on the future of customer service. The conference will feature presentations from leaders in various AI and data organizations, as well as a panel debate. Statistics are presented showing the growing importance and impact of AI and chatbots on customer service interactions and cost savings over the coming years. The AMAOS project from the University of Copenhagen is also introduced, which focuses on advanced machine learning for automated omni-channel customer support.
The document discusses a project aimed at improving quality of life for citizens with affective disorders like depression. It outlines a vision called "Psyche" that aims to anticipate and alleviate acute depression through a digital platform. A configuration table presents the rationale, strategy, and tactics for a prospect to realize this vision, including leveraging the user's digital diary and questionnaire responses to detect emerging depressive episodes and provide alleviation measures. The table identifies challenges like ineffective intervention and underused platform potential, noting that anticipation works but could be improved and alleviation measures are sometimes weak or misplaced.
This document discusses spasticity management and Inerventions' product called Mollii, which uses electrical therapy to reduce spasticity and improve motor control for people with conditions like cerebral palsy, stroke, and multiple sclerosis. Mollii is a medical device suit with electrodes that can be individually programmed. Clinical studies in Sweden and Denmark show that Mollii reduces spasticity and facilitates voluntary movement, helping users to live more freely. Inerventions' vision is for Mollii to become a natural first choice for non-invasive spasticity management.
This document discusses several robots that can be used in healthcare settings including Giraff, Toyota Human Support Robot, and OriHime. It also mentions technologies such as the R3 platform, robot control by gaze from bed, and positioning with roof fiducials. The document appears to cover different robots available for healthcare as well as some of their capabilities and technologies involved in their operation.
This document discusses unit testing and code coverage measurement in the software development process. It describes refactoring code to enable unit testing by adding assert macros and a test program. The document also mentions measuring test coverage to ensure code is thoroughly tested during the refactoring process.
Kliniske retningslinier - fra tekst til it-understøttelse, hvor ligger faldgruberne? af Karen Marie Lyng, IMT, Region Hovedstaden
1. Kliniske retningslinjer -
fra tekst til it-understøttelse,
hvor ligger faldgruberne?
Temadag om sammenhængende patientforløb,
sundheds-processer og it
20. april 2012
2. Agenda
• Baggrund og definitioner
• Retningslinjer
• Arbejde
• IT-understøttelse
• Relationer mellem retningslinjer, IT og klinisk
arbejde
• Udfordringer ved etablering af retningslinje baseret
klinisk IT
•
3. Vidensbaseret patientbehandling
Status:
• Sundhedssektoren døjer med
1
• Variation
2
• Lang implementeringstid for ny viden
3
• Fejl og utilsigtede hændelser
4
• Enorm mængde sundhedsfaglig viden
5
• Ingen effekt af kliniske retningslinjer!
6, 7
• Krav om ‘just in time’ viden
1) Kjellberg 2005
2) Shojana 2007
3) Kohn 2000
4) Davis 2006
5) Farmer 2008
6) Smith
7) Bates 2003
4. Grundlag for IT processtøtte
Informations
teknologi
Retningslinjer Arbejde
5. Kliniske retningslinjer
Systematisk udarbejdede udsagn, der kan
bruges af fagpersoner og patienter, når
der skal træffes beslutning om passende
og korrekt sundhedsfaglig ydelse i
specifikke kliniske situationer.
(DSKS 2003: Sundhedsvæsenets kvalitetsbegreber og definitioner)
11. Klinisk IT
Hardware Software
• Eksisterende fysiske • Mange systemer
rammer • Informationsmodeller
• grænsesnit
• Tilgængelighed
• Pris • Multi user usability
• Multiple formater • Adgang kun til relevante
data
• Kontekst forhold
• Logning
• Hygiejne,
robusthed,
sikkerhed……
• Performance 24 x 7
12. Information
Technology
IT
un
g
rin
de
is e
rs
g
Ko
in
tø
rd
r
tte
nt
ise
da
e
ls
at
xt
an
e
m
st
to
Au
Vejledning
Retningslinje Arbejde
Kontext
13. Vidensbasis for klinisk arbejde
Domæne specific viden
Domæne
Klinisk raportering Retningslinjer
Organisations specifik viden
Organisation
Standard dokumentation (SFI) Standard planer
Patient specific information
Patient
Patient data Patient plan
Aktiviteter i klinisk praksis
14. Computeriserede kliniske retningslinjer
Bør være:
• Aktivitetsspecifikke
• Overblik - detail
• Tilstede på behandlingssted
• Indlejret i arbejdspraksis
• Fleksible
• Understøtte koordination af arbejdet
• Automatisererede når det er hensigtsmæssigt
• Designet så lokale tilpasninger er mulige
• Designet til at understøtte strategiske mål
• Hastighed – hastighed - hastighed
15. Væsentlige udfordringer
• Der findes ingen ”standard” patienter
• Planer ændres under eksekvering
• Patientplaner har en tæt relation til indsamling og præsentation
af data
• Det tager lang tid at udforme standardplaner
• Der sker til stadigheder ændringer i kliniske retningslinjer
• Der sker til stadighed ændringer i organisation og ressourcer
• Kliniske retningslinjer - standardplaner - patientplaner skal
kunne udtrykkes standardiseret og højt struktureret for at være
computerlæsbare/computer eksekverbare
• Metoder til validering af at planer omsat til computer læsbare
planer er i overensstemmelse med forlægget