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conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
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This notice is to inform everyone that follows or interacts with any of our websites that we have always been GDPR compliant and will continue to be GDPR compliant in the future. This applies to all of our websites and associated mailing lists and video platforms, all of which are housed under...
www.hopegirlblog.com/2018/05/24/fix-the-world-qeg-clean-e...
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conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
Ο Κύκλος Ιδεών για την Εθνική Ανασυγκρότηση σε συνεργασία με το Ίδρυμα Διεθνών Νομικών Μελετών- Καθηγητού Ηλία Κρίσπη και με την υποστήριξη της Ελληνοαμερικανικής Ένωσης, πραγματοποίησε ανοιχτή συζήτηση με θέμα:
«Προστασία Προσωπικών Δεδομένων - Ηλεκτρονική Ταυτοποίηση»
Διαχείριση Προσωπικών Δεδομένων μετά την υιοθέτηση του νέου Γενικού Κανονισμού (GDPR) και Ηλεκτρονική Ταυτοποίηση με τη χρήση του δικτύου eIDAS (eID_EU): Επιχειρησιακές, τεχνικές και θεσμικές συνέπειες
την Τετάρτη 14 Μαρτίου 2018, στο Θέατρο της Ελληνοαμερικανικής Ένωσης
Στη συζήτηση συμμετέχουν:
Λίλιαν Μήτρου, Πανεπιστήμιο Αιγαίου - Πολυτεχνική Σχολή
Κωνσταντίνος Χριστοδούλου, Πανεπιστήμιο Αθηνών - Νομική Σχολή
Αντώνης Στασής, Υπουργείο Διοικητικής Ανασυγκρότησης - Διεύθυνση Ηλεκτρονικής Διακυβέρνησης
Χρυσούλα Μιχαηλίδου, ΕΕΤΤ, Νομική Υπηρεσία
Γιώργος Παπασταματίου, FORTH-CRS
Κώστας Γκρίτσης, MICROSOFT
Φερενίκη Παναγοπούλου-Κουτνατζή, Πάντειο Πανεπιστήμιο – Σχολή Δημόσια Διοίκησης
Συντονίζει ο Πέτρος Καβάσαλης, Πανεπιστήμιο Αιγαίου - Πολυτεχνική Σχολή & Κύκλος Ιδεών για την Εθνική Ανασυγκρότηση
ekyklos.gr/ev/581-14-3-2018-prostasia-dedomenon-ilektroni...
The healthcare industry has witnessed the remarkable growth of artificial intelligence (AI), which has found diverse applications. As technology advances, AI’s potential in healthcare continues to expand. Nevertheless, certain limitations currently hinder the seamless integration of AI into existing healthcare systems.
AI is used in healthcare datasets to analyze data, provide clinical decision support, detect diseases, personalize treatment, monitor health, and aid in drug discovery. It enhances patient care, improves outcomes, and drives advancements in the healthcare industry. Many AI services such as Amazon Comprehend Medical, Google Cloud Healthcare API, John Snow Labs provide pre-built models. Due to the variety of medical data and requirements for accuracy human in the loop techniques are important to safeguard accuracy. However, the success of AI and ML models largely depends on the quality of the data they are trained on, necessitating reliable and accurate data labelling services.
Challenges in applying AI in Healthcare
Extensive testing of AI is necessary to prevent diagnostic errors, which account for a significant portion of medical errors and result in numerous deaths each year. While AI shows promise for accurate diagnostics, concerns remain regarding potential mistakes. Ensuring representative training data and effective model generalization are crucial for successful AI integration in healthcare.
In the healthcare sector, ensuring the privacy and security of patient data is paramount, as it not only fosters trust between healthcare providers and patients, but also complies with stringent regulatory standards such as HIPAA, promoting ethical, responsible data handling practices.
Lack of High-Quality Labeled datasets
Achieving a high quality labeled medical dataset poses several challenges, including:
Medical Labeling Skills: -Properly labeling medical data requires specialized domain knowledge and expertise. Medical professionals or trained annotators with a deep understanding of medical terminology and concepts are necessary to ensure accurate and meaningful annotations.
Managing Labeling Quality: -Maintaining high-quality labeling is crucial for reliable and trustworthy datasets. Ensuring consistency, accuracy, and minimizing annotation errors is challenging, as medical data can be complex and subject to interpretation. Robust quality control measures, including double-checking annotations and inter-annotator agreement, are necessary to mitigate labeling inconsistencies.
Managing the Cost of Labeling: -Labeling medical datasets can be a resource-intensive process, both in terms of time and cost. Acquiring sufficient labeled data may require significant financial investment, especially when specialized expertise is involved. Efficient labeling workflows, leveraging automation when feasible, can help manage throughput and reduce costs without compromising data quality.
Data Privacy and Security: -Safeguarding patient privacy and ensuring secure handling of sensitive medical data is crucial when collecting and labeling datasets.
Data Diversity and Representativeness: -Ensuring that the dataset captures the diversity of medical conditions, demographics, and healthcare settings is essential for building robust and unbiased AI models.
Best practices to manage medical labeling projects
Addressing these challenges requires a combination of domain expertise, quality control measures, and optimizing labeling processes to strike a balance between accuracy, cost-effectiveness, and dataset scale.
At Objectways we follow the Best Practices in medical labeling which include
Adherence to Guidelines: -Familiarize labeling teams with clear and comprehensive guidelines specific to the medical domain. Thoroughly understanding the guidelines ensures consistent and accurate labeling.
Conducting KPT (Knowledge, Process, Test): -Provide comprehensive training to labeling teams on medical concepts, terminology, and labeling procedures. Regular knowledge assessments and testing help evaluate proficiency of labeling teams and ensure continuous improvement.
Robust Team Structure: -We have established a structured team comprising labeling personnel, spot Quality Assurance (QA) reviewers, and dedicated QA professionals. This structure promotes accountability, efficient workflow, and consistent quality.
Quality Metrics: -We have implemented appropriate quality metrics such as precision, recall, and F1 score to assess labeling accuracy. We regularly monitor and track these metrics to identify areas for improvement and maintain high-quality standards.
Continuous Feedback Loop: -We have established a feedback mechanism where labeling teams receive regular feedback on their performance. This helps address any inconsistencies, clarify guidelines, and improve overall labeling accuracy.
Quality Control and Spot QA: - By implementing robust quality control measures, including periodic spot QA reviews by experienced reviewers, helps identify and rectify any labeling errors, ensures adherence to guidelines, and maintains high labeling quality.
Data Security and Privacy: - To validate our commitment to security and privacy controls, we have obtained the following formal certifications SOC2 Type2, ISO 27001, HIPAA, and GDPR. These certifications affirm our dedication to safeguarding customer data. Our privacy and security programs continue to expand, adhering to Privacy by Design principles and incorporating industry standards and customer requirements from various sectors.
Summary
At Objectways we have a team of certified annotators, including medical professionals such as nurses, doctors, and medical coders. Our experience includes working with top Cloud Medical AI providers, Healthcare providers and Insurance companies, utilizing advanced NLP techniques to create top-notch training sets and conduct human reviews of pre-labels across a wide variety of document formats and ontologies, such as call transcripts, patient notes, and ICD documents. Our DICOM data labeling services for computer vision cover precise annotation of medical images, including CT scans, MRIs, and X-rays and expert domain knowledge in radiology to ensure the accuracy and quality of labeled data.
In summary, the effectiveness of AI and ML models hinges significantly on the calibre of the data used for training, underscoring the need for dependable and precise data labeling services. Please contact sales@objectways.com to enhance your AI Model Performance
Anexas provides the best GDPR clasroom training in Mysore. You can pursue GDPR Courses now in your own city, Mysore.
The GDPR courses are delivered online also so that the students can pursue the course content anywhere at any time. The flexibility easy accessibility in learning process made our online GDPR courses very popular useful not only in Mysore but also in many others cities. Anexas has students from Mysore who have enrolled for GDPR courses are from industries like Automobiles, IT, ITES, Manufacturing, Healthcare, Banking Finance, Entertainment, Retail etc. Anexas GDPR training is considered to be one of the best online training programs conducted in Mysore.
Engineering or Post-Graduate students of Mysore have a greater edge when they have GDPR Certification added to their profiles. GDPR certified will be the first ones to be considered for the job over the others.
www.anexas.net/certified-gdpr-data-protection-training-my...
General Data Protection Regulation || Image Source: www.urbannetwork.co.uk/wp-content/uploads/2017/02/What-GD...
Anexas provides the best GDPR clasroom training in Kolkata. You can pursue GDPR Courses now in your own city, Kolkata.
The GDPR courses are delivered online also so that the students can pursue the course content anywhere at any time. The flexibility easy accessibility in learning process made our online GDPR courses very popular useful not only in Kolkata but also in many others cities. Anexas has students from Kolkata who have enrolled for GDPR courses are from industries like Automobiles, IT, ITES, Manufacturing, Healthcare, Banking Finance, Entertainment, Retail etc. Anexas GDPR training is considered to be one of the best online training programs conducted in Kolkata.
Engineering or Post-Graduate students of Kolkata have a greater edge when they have GDPR Certification added to their profiles. GDPR certified will be the first ones to be considered for the job over the others.
www.anexas.net/certified-gdpr-data-protection-training-ko...
conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
conference, audience, speaker, delegate, exhibitor, trade, Glasgow, University of Strathclyde, GDPR, Technology and Innovation Centre, podium, data, legislation, privacy, Holyrood
In these uncertain times, where health concerns are our most pressing challenge, there still must remain a focus on business-related concerns. Travel restrictions caused by the health crisis are affecting the performance of a business, with remote technologies required at a level never previously anticipated.
While these technologies support the ability of many of us to work and collaborate remotely, legal departments, law firms, and government agencies must ensure continued compliance with records retention requirements, data privacy laws (like CCPA – California Consumer Privacy Act and GDPR), and other operational regulations. Also, remote technologies used to share business information could be subject to discovery requests in civil litigation, requiring legal professionals to maintain easy access to their data.
Read full article at www.knovos.com/experts-weigh-in-on-the-new-normal-of-work...