In the past decade, there has been a significant increase in the use of Data Monitoring
Committees (DMC) and Adaptive Designs (AD) in clinical trials. While the monitoring of safety
data by a formal committee is not required for all clinical trials, it has become the norm to have
a formal DMC conduct periodic safety reviews for any controlled trial that evaluates treatments
intended to prolong life or reduce risk of major adverse health outcomes, or for trials that
compare rates of mortality or major morbidity. Confirmatory, pivotal, and adaptive design trials
have more complex operational issues requiring an external and independent DMC. The DMC
may have access to unblinded interim data, be required to make expert recommendations
about how the trial should continue, and then ensure that planned adaptations are
implemented as outlined in the protocol without involving the sponsor or exposing it to
unblinded data or results.
This added complexity creates a challenge and a question: how can the DMC, statisticians, and
sponsor effectively communicate, share blinded and unblinded data, perform analyses, and
implement adaptations without introducing operational bias or compromising the integrity of
the trial? One solution is to utilize a sophisticated computer system that can provide the
security and necessary firewalls to ensure that interim data is only accessible to those it is
intended for, that the rules and processes outlined in the protocol and DMC charter are
enforced, and that communication between the DMC and sponsor is effectively facilitated while
protecting the integrity of the trial and preventing the introduction of operational bias.
The system must also provide an audit trail that tracks “who saw what and when” providing
evidence to regulatory authorities that the protocol was strictly followed with a minimal
possibility of bias. This white paper describes the computer system, ACES, which Cytel has built,
that makes all of this possible. ACES (Access Control Execution System) has been purpose-built
to address the operational complexities inherent in adaptive design and pivotal clinical trials.
White paper: Functional Requirements for Enterprise Clinical Data Management:...Carestream
As healthcare organizations plan for the future growth and integration of clinical
data into their IT ecosystems, it’s crucial to clearly define the functional requirements spanning the needs of users across the enterprise. This white paper provides an overview of the key functional requirements. To learn more visit carestream.com/clinical-collaboration
Improve Patient Care and Reduce IT Costs with Vendor Neutral Archiving and Cl...EMC
This paper illustrates how Vendor Neutral Archive combined Atmos cloud storage enable healthcare organizations to break down PACS silos to reduce storage and archive costs, and provide secure, anywhere access to medical images on any device at the point of care.
Late Binding in Data Warehouses: Desiging for Analytic AgilityHealth Catalyst
Listen to Part 2 of the Late-Binding (TM) Data Warehouse webinar, a separate webinar focused on answering detailed follow-up questions generated from the first Late-Binding (TM) Data Warehouse webinar.
Late Binding: The New Standard For Data WarehousingHealth Catalyst
Join Dale Sanders as he explains the concepts behind the Late-Binding (TM) Data Warehouse for healthcare. In this webinar, Dale covers 5 main concepts including 1) The history and concept of "binding" in software and data engineering, 2) Examples of data binding in healthcare, 3) the two tests for early binding (comprehensive and persistent agreement), 4) the six points of binding in data warehouse design (including a comparison of data modeling and late binding), and 5) the importance of binding in analytic progressions (including the eight levels of analytic adoption in healthcare).
White paper: Functional Requirements for Enterprise Clinical Data Management:...Carestream
As healthcare organizations plan for the future growth and integration of clinical
data into their IT ecosystems, it’s crucial to clearly define the functional requirements spanning the needs of users across the enterprise. This white paper provides an overview of the key functional requirements. To learn more visit carestream.com/clinical-collaboration
Improve Patient Care and Reduce IT Costs with Vendor Neutral Archiving and Cl...EMC
This paper illustrates how Vendor Neutral Archive combined Atmos cloud storage enable healthcare organizations to break down PACS silos to reduce storage and archive costs, and provide secure, anywhere access to medical images on any device at the point of care.
Late Binding in Data Warehouses: Desiging for Analytic AgilityHealth Catalyst
Listen to Part 2 of the Late-Binding (TM) Data Warehouse webinar, a separate webinar focused on answering detailed follow-up questions generated from the first Late-Binding (TM) Data Warehouse webinar.
Late Binding: The New Standard For Data WarehousingHealth Catalyst
Join Dale Sanders as he explains the concepts behind the Late-Binding (TM) Data Warehouse for healthcare. In this webinar, Dale covers 5 main concepts including 1) The history and concept of "binding" in software and data engineering, 2) Examples of data binding in healthcare, 3) the two tests for early binding (comprehensive and persistent agreement), 4) the six points of binding in data warehouse design (including a comparison of data modeling and late binding), and 5) the importance of binding in analytic progressions (including the eight levels of analytic adoption in healthcare).
HySynth Clinical Data Repository is used for storing, integrating ,managing and reporting on clinical studies.
It enables pooling of clinical and nonclinical data from multiple sources into a single environment. Better regulatory compliance with comprehensive security, an audit trail, and traceability, More-informed decision-making through pooling and analysis of clinical and nonclinical data
CDR has been developed to revolutionize ability to:
- Address complex health authority questions quickly and completely
- Produce CDISC compliant submissions
- Review safety data in real-time, mine our overall database for scientific and commercial queries
At HySynth provide,
- Business case development and cost analysis
- Requirements and design management
- Best practice analysis and recommendations
- Installation and configuration
- Oracle CDA and LSH pilots and proofs of concept
- Hosting
- Oracle CDA and LSH implementation
- CDA and LSH validation
- CDA and LSH training
- CDA and LSH extension development
LST on the following applications
- Argus Safety Suite
- Oracle Clinical / Remote Data Capture (RDC) /
- Thesaurus Management System (TMS)
- Oracle Inform EDC / Central Designer / Central Coding
- Life Sciences Data Hub (LSH)
- Oracle Data Management Workbench (DMW)
- Oracle Clinical Development Analytics (CDA)
- Adverse Event Reporting System (AERS)
- SAS
E-clinical providers are fighting to reposition and re-assert themselves amid changing customer needs...article by Peter Mansell, interviewing Steve Kent, President of Parexel and Laurence Birch, Chairman of DATATRAK International. www.Pharmatimes.com
Big Data Analytics for Healthcare Decision Support- Operational and ClinicalAdrish Sannyasi
Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
This webinar will focus on the technical and practical aspects of creating and deploying predictive analytics. We have seen an emerging need for predictive analytics across clinical, operational, and financial domains. One pitfall we’ve seen with predictive analytics is that while many people with access to free tools can develop predictive models, many organizations fail to provide a sufficient infrastructure in which the models are deployed in a consistent, reliable way and truly embedded into the analytics environment. We will survey techniques that are used to get better predictions at scale. This webinar won’t be an intense mathematical treatment of the latest predictive algorithms, but will rather be a guide for organizations that want to embed predictive analytics into their technical and operational workflows.
Topics will include:
Reducing the time it takes to develop a model
Automating model training and retraining
Feature engineering
Deploying the model in the analytics environment
Deploying the model in the clinical environment
In this report, ISR leverages the insights and real-world experiences investigative sites have with electronic medical records (EMRs) and clinical trials. The report examines how sites currently use EMRs for various clinical trial activities and provides recommendations to improve trial efficiency.
The role of the FAIR Guiding Principles in a Learning Health SystemMichel Dumontier
The learning health system (LHS) is a concept for a socio-technological system that continuously improves the delivery of health care by coupling biomedical research with practice- and evidence- based medicine. Key aspects of the LHS are collecting, integrating, and analyzing data from different sources. While the increased digitalisation of healthcare is creating new data sources, these remain hard to find and use, let alone make use of as part of intelligent systems for the benefit of patients, healthcare providers, and researchers. This talk will examine recent developments towards making key parts of the LHS, such as clinical practice guidelines, Findable, Accessible, Interoperable, and Reusable (FAIR).
Regulating eDiaries from Planning to Retention of Archival eSource Records
by Stephen A. Raymond, PhD
Chief Scientific Officer and Founder
PHT Corporation
Frost & Sullivan 2016 Innovation Award Research Summary for New Product Innov...Carestream
Frost and Sullivan’s 10-step process for evaluating candidates for the award.
Frost & Sullivan has awarded Carestream Health its 2016 North America Frost & Sullivan Award for New Product Innovation Leadership for innovation focused on value-based imaging that solves real-life problems and addresses unmet customer needs. This document summarizes the research and processes used by F&S for naming the winner.
Learn more about Carestream Health's medical imaging products at http://www.carestream.com/medical
#Innovation
#Aim2innovate
#winner
Planning the implementation of an EMR or EHR, then you need to understand the basics of defining your clinical workflow. This presentation was made at a variety of medical conferences
Imaging in the Cloud: A New Era for RadiologyCarestream
A look at how cloud computing is helping the medical imaging industry. The cloud is changing old mindsets, and allowing technologies, such as a vendor-neutral archive (VNA), to make health facilities more efficient and provide higher quality care.
A crucial stage in clinical research is clinical data management CDM , which produces high quality, reliable, and statistically sound data from clinical trials. This results in a significantly shorter period of time between drug development and marketing. Team members of CDM are laboriously involved in all stages of clinical trials right from commencement to completion. They should be able to sustain the quality standards set by CDM processes by having sufficient process expertise. colorful procedures in CDM including Case Report Form CRF designing, CRF reflection, database designing, data entry, data confirmation, distinction operation, medical coding, data birth, and database locking are assessed for quality at regular intervals during a trial. In the present script, theres an increased demand to ameliorate the CDM norms to meet the nonsupervisory conditions and stay ahead of the competition by means of brisk commercialization of products. With the perpetration of nonsupervisory biddable data operation tools, the CDM platoon can meet these demands. also, its getting obligatory for companies to submit the data electronically. CDM professionals should meet applicable prospects and set norms for data quality and also have the drive to acclimatize to the fleetly changing technology. This composition highlights the processes involved and provides the anthology an overview of the tools and norms espoused as well as the places and liabilities in CDM. Syed Shahnawaz Quadri | Syeda Saniya Ifteqar | Syed Shafa Raoof "Data Management in Clinical Research" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55050.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/other/55050/data-management-in-clinical-research/syed-shahnawaz-quadri
HySynth Clinical Data Repository is used for storing, integrating ,managing and reporting on clinical studies.
It enables pooling of clinical and nonclinical data from multiple sources into a single environment. Better regulatory compliance with comprehensive security, an audit trail, and traceability, More-informed decision-making through pooling and analysis of clinical and nonclinical data
CDR has been developed to revolutionize ability to:
- Address complex health authority questions quickly and completely
- Produce CDISC compliant submissions
- Review safety data in real-time, mine our overall database for scientific and commercial queries
At HySynth provide,
- Business case development and cost analysis
- Requirements and design management
- Best practice analysis and recommendations
- Installation and configuration
- Oracle CDA and LSH pilots and proofs of concept
- Hosting
- Oracle CDA and LSH implementation
- CDA and LSH validation
- CDA and LSH training
- CDA and LSH extension development
LST on the following applications
- Argus Safety Suite
- Oracle Clinical / Remote Data Capture (RDC) /
- Thesaurus Management System (TMS)
- Oracle Inform EDC / Central Designer / Central Coding
- Life Sciences Data Hub (LSH)
- Oracle Data Management Workbench (DMW)
- Oracle Clinical Development Analytics (CDA)
- Adverse Event Reporting System (AERS)
- SAS
E-clinical providers are fighting to reposition and re-assert themselves amid changing customer needs...article by Peter Mansell, interviewing Steve Kent, President of Parexel and Laurence Birch, Chairman of DATATRAK International. www.Pharmatimes.com
Big Data Analytics for Healthcare Decision Support- Operational and ClinicalAdrish Sannyasi
Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
This webinar will focus on the technical and practical aspects of creating and deploying predictive analytics. We have seen an emerging need for predictive analytics across clinical, operational, and financial domains. One pitfall we’ve seen with predictive analytics is that while many people with access to free tools can develop predictive models, many organizations fail to provide a sufficient infrastructure in which the models are deployed in a consistent, reliable way and truly embedded into the analytics environment. We will survey techniques that are used to get better predictions at scale. This webinar won’t be an intense mathematical treatment of the latest predictive algorithms, but will rather be a guide for organizations that want to embed predictive analytics into their technical and operational workflows.
Topics will include:
Reducing the time it takes to develop a model
Automating model training and retraining
Feature engineering
Deploying the model in the analytics environment
Deploying the model in the clinical environment
In this report, ISR leverages the insights and real-world experiences investigative sites have with electronic medical records (EMRs) and clinical trials. The report examines how sites currently use EMRs for various clinical trial activities and provides recommendations to improve trial efficiency.
The role of the FAIR Guiding Principles in a Learning Health SystemMichel Dumontier
The learning health system (LHS) is a concept for a socio-technological system that continuously improves the delivery of health care by coupling biomedical research with practice- and evidence- based medicine. Key aspects of the LHS are collecting, integrating, and analyzing data from different sources. While the increased digitalisation of healthcare is creating new data sources, these remain hard to find and use, let alone make use of as part of intelligent systems for the benefit of patients, healthcare providers, and researchers. This talk will examine recent developments towards making key parts of the LHS, such as clinical practice guidelines, Findable, Accessible, Interoperable, and Reusable (FAIR).
Regulating eDiaries from Planning to Retention of Archival eSource Records
by Stephen A. Raymond, PhD
Chief Scientific Officer and Founder
PHT Corporation
Frost & Sullivan 2016 Innovation Award Research Summary for New Product Innov...Carestream
Frost and Sullivan’s 10-step process for evaluating candidates for the award.
Frost & Sullivan has awarded Carestream Health its 2016 North America Frost & Sullivan Award for New Product Innovation Leadership for innovation focused on value-based imaging that solves real-life problems and addresses unmet customer needs. This document summarizes the research and processes used by F&S for naming the winner.
Learn more about Carestream Health's medical imaging products at http://www.carestream.com/medical
#Innovation
#Aim2innovate
#winner
Planning the implementation of an EMR or EHR, then you need to understand the basics of defining your clinical workflow. This presentation was made at a variety of medical conferences
Imaging in the Cloud: A New Era for RadiologyCarestream
A look at how cloud computing is helping the medical imaging industry. The cloud is changing old mindsets, and allowing technologies, such as a vendor-neutral archive (VNA), to make health facilities more efficient and provide higher quality care.
A crucial stage in clinical research is clinical data management CDM , which produces high quality, reliable, and statistically sound data from clinical trials. This results in a significantly shorter period of time between drug development and marketing. Team members of CDM are laboriously involved in all stages of clinical trials right from commencement to completion. They should be able to sustain the quality standards set by CDM processes by having sufficient process expertise. colorful procedures in CDM including Case Report Form CRF designing, CRF reflection, database designing, data entry, data confirmation, distinction operation, medical coding, data birth, and database locking are assessed for quality at regular intervals during a trial. In the present script, theres an increased demand to ameliorate the CDM norms to meet the nonsupervisory conditions and stay ahead of the competition by means of brisk commercialization of products. With the perpetration of nonsupervisory biddable data operation tools, the CDM platoon can meet these demands. also, its getting obligatory for companies to submit the data electronically. CDM professionals should meet applicable prospects and set norms for data quality and also have the drive to acclimatize to the fleetly changing technology. This composition highlights the processes involved and provides the anthology an overview of the tools and norms espoused as well as the places and liabilities in CDM. Syed Shahnawaz Quadri | Syeda Saniya Ifteqar | Syed Shafa Raoof "Data Management in Clinical Research" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55050.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/other/55050/data-management-in-clinical-research/syed-shahnawaz-quadri
Challenges and Opportunities Around Integration of Clinical Trials DataCitiusTech
Conducting a Clinical Trial is a complex process, consisting of activities such as protocol preparation, site selection, approval of various authorities, meticulous collection and management of data, analysis and reporting of the data collected
Each activity is benefited from the development of point applications which ease the process of data collection, reporting and decision making. The recent advancements in mobile technologies and connectivity has enabled the generation and exchange of a lot more data than previously anticipated. However, the lack of interoperability and proper planning to leverage this data, still acts as a roadblock in allowing organizations truly harness their data assets. This document will help life sciences IT professionals and decision makers understand challenges and opportunities around clinical data integration
Who needs fast data? - Journal for Clinical Studies KCR
How “no news” during the life of a trial is bad news, and what data management (among other things) can do to help when ensuring access to fast data? Get to know this and more about smart e-solutions in the newest article of Kaia Koppel, Associate Director, Biometrics & Clinical Trial Data Execution Systems at KCR, in the recent issue of Journal for Clinical Studies (p.40-21).
Integrate RWE into clinical developmentIMSHealthRWES
With greater application of RWE throughout the pharmaceutical
lifecycle, learnings are emerging that offer guidance for
approaches to derive the maximum value. This article captures
the author’s experience at a leading international biotech, with
insights for smoothing RWE assimilation into clinical
development and realizing the benefits it brings.
Dynamic Rule Base Construction and Maintenance Scheme for Disease Predictionijsrd.com
Business and healthcare application are tuned to automatically detect and react events generated from local are remote sources. Event detection refers to an action taken to an activity. The association rule mining techniques are used to detect activities from data sets. Events are divided into 2 types' external event and internal event. External events are generated under the remote machines and deliver data across distributed systems. Internal events are delivered and derived by the system itself. The gap between the actual event and event notification should be minimized. Event derivation should also scale for a large number of complex rules. Attacks and its severity are identified from event derivation systems. Transactional databases and external data sources are used in the event detection process. The new event discovery process is designed to support uncertain data environment. Uncertain derivation of events is performed on uncertain data values. Relevance estimation is a more challenging task under uncertain event analysis. Selectability and sampling mechanism are used to improve the derivation accuracy. Selectability filters events that are irrelevant to derivation by some rules. Selectability algorithm is applied to extract new event derivation. A Bayesian network representation is used to derive new events given the arrival of an uncertain event and to compute its probability. A sampling algorithm is used for efficient approximation of new event derivation. Medical decision support system is designed with event detection model. The system adopts the new rule mapping mechanism for the disease analysis. The rule base construction and maintenance operations are handled by the system. Rule probability estimation is carried out using the Apriori algorithm. The rule derivation process is optimized for domain specific model.
ICU Patient Deterioration Prediction : A Data-Mining Approachcsandit
A huge amount of medical data is generated every da
y, which presents a challenge in analysing
these data. The obvious solution to this challenge
is to reduce the amount of data without
information loss. Dimension reduction is considered
the most popular approach for reducing
data size and also to reduce noise and redundancies
in data. In this paper, we investigate the
effect of feature selection in improving the predic
tion of patient deterioration in ICUs. We
consider lab tests as features. Thus, choosing a su
bset of features would mean choosing the
most important lab tests to perform. If the number
of tests can be reduced by identifying the
most important tests, then we could also identify t
he redundant tests. By omitting the redundant
tests, observation time could be reduced and early
treatment could be provided to avoid the risk.
Additionally, unnecessary monetary cost would be av
oided. Our approach uses state-of-the-art
feature selection for predicting ICU patient deteri
oration using the medical lab results. We
apply our technique on the publicly available MIMIC
-II database and show the effectiveness of
the feature selection. We also provide a detailed a
nalysis of the best features identified by our
approach.
ICU PATIENT DETERIORATION PREDICTION: A DATA-MINING APPROACHcscpconf
A huge amount of medical data is generated every day, which presents a challenge in analysing
these data. The obvious solution to this challenge is to reduce the amount of data without
information loss. Dimension reduction is considered the most popular approach for reducing
data size and also to reduce noise and redundancies in data. In this paper, we investigate the
effect of feature selection in improving the prediction of patient deterioration in ICUs. We
consider lab tests as features. Thus, choosing a subset of features would mean choosing the
most important lab tests to perform. If the number of tests can be reduced by identifying the
most important tests, then we could also identify the redundant tests. By omitting the redundant
tests, observation time could be reduced and early treatment could be provided to avoid the risk.
Additionally, unnecessary monetary cost would be avoided. Our approach uses state-of-the-art
feature selection for predicting ICU patient deterioration using the medical lab results. We
apply our technique on the publicly available MIMIC-II database and show the effectiveness of
the feature selection. We also provide a detailed analysis of the best features identified by our
approach.
White paper explores Intel’s latest SSD technology, new Carestream solutions, the impact for PACS, and a look at the future of medical imaging data, access, storage and analysis.
Workflow Continuity—Moving Beyond Business Continuityin a Mu.docxambersalomon88660
Workflow Continuity—Moving Beyond Business Continuity
in a Multisite 24–7 Healthcare Organization
Brian J. Kolowitz & Gonzalo Romero Lauro &
Charles Barkey & Harry Black & Karen Light &
Christopher Deible
Published online: 6 July 2012
# Society for Imaging Informatics in Medicine 2012
Abstract As hospitals move towards providing in-house
24×7 services, there is an increasing need for information
systems to be available around the clock. This study inves-
tigates one organization’s need for a workflow continuity
solution that provides around the clock availability for in-
formation systems that do not provide highly available
services. The organization investigated is a large multifacil-
ity healthcare organization that consists of 20 hospitals and
more than 30 imaging centers. A case analysis approach was
used to investigate the organization’s efforts. The results
show an overall reduction in downtimes where radiologists
could not continue their normal workflow on the integrated
Picture Archiving and Communications System (PACS)
solution by 94 % from 2008 to 2011. The impact of un-
planned downtimes was reduced by 72 % while the impact
of planned downtimes was reduced by 99.66 % over the
same period. Additionally more than 98 h of radiologist
impact due to a PACS upgrade in 2008 was entirely elimi-
nated in 2011 utilizing the system created by the workflow
continuity approach. Workflow continuity differs from high
availability and business continuity in its design process and
available services. Workflow continuity only ensures that
critical workflows are available when the production system
is unavailable due to scheduled or unscheduled downtimes.
Workflow continuity works in conjunction with business
continuity and highly available system designs. The results
of this investigation revealed that this approach can add
significant value to organizations because impact on users
is minimized if not eliminated entirely.
Keywords Workflow continuity . Business continuity .
PACS planning . PACS integration . PACS downtime
procedures . PACS administration . PACS . PACS service .
Software design . Systems integration . Workflow .
Productivity . Management information systems .
Information system . Image retrieval . Health level 7 (HL7) .
Efficiency
Background
Recently, the US government mandated the use of health
information technology for healthcare providers [1]. The
legislation outlines financial penalties for providers that
choose not to adopt technologies as well as benefits for
those that do adopt the technologies. As the adoption of
health information technology increases, so will the need for
information systems that allow critical organizational work-
flows to continue when those systems are unavailable due to
either scheduled or unscheduled system downtimes.
This paper is a case analysis of one organization’s solu-
tion to a need for a system that provides workflow continu-
ity around the clock. Workflow continuity moves beyond.
A unified platform providing functionality based on role is a logical progression in eClinical technology development, with the majority of sponsors/CROs preferring and supporting this evolution.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.