• 9th December 2020

    2 - 6 PM

    Online

    IBM Workshop Series:

    Reimagining clinical care with Artificial Intelligence:

    Understand the voice of a patient

     

     

    Unlocking the value of healthcare information:

    How to Apply Fully Homomorphic Encryption to Easily Drive Analytics Data Sharing Innovation in the Healthcare Industry

     

    Free but registration needed

  • Registration is closed with 100+ registered!

     

    IBM Workshop Series:

     

    Reimagining clinical care with Artificial Intelligence

    Understand the voice of a patient

    2-4 PM 9th Dec (Online)

     

    Instructors: Dileep Rangan; Sudesh Krishnamoorthy and Chan Chung Kit

    Synopsis: Health care organizations need to focus on making AI operational in order to deliver improved care and engagement with their patients and staff and obtain value from their AI investments. In this section AI Data & AI expert labs, the group charged with developing solutions and implementing them for our clients, will walk through two key components of the engagement and AI lead insights activities. Specifically, IBM will discuss and demonstrate the capabilities of AI speech understanding, including how non-IT staff can train IBM's low code speech to text solution, and how you can train IBM speech to text to understand the linguistic nuances of your business.

     

    In the second part of the talk we will discuss and demonstrate how you can derive insights from health care data, such as doctors notes, case references, etc. using IBM's leading edge AI natural language understanding capabilities. We will demonstrate possible use cases and ease of build by utilizing one of IBM's acceleration offerings, Annotator for Clinical Data (ACD). ACD was built to enable you to more quickly teach Watson the language of the medical domain.

     

    Through the session we will put these capabilities in the context of designing and building solutions to address your needs and how to bring your AI to life to start solving problems for you every day.

  • Unlocking the Value of Healthcare Information

    How to Apply Fully Homomorphic Encryption to Easily Drive Analytics Data Sharing Innovation in the Healthcare Industry

    4-6 PM 9th Dec (Online)

    Instructors: John Buselli​ and Omri SoceanuI

    Synopsis: More and more healthcare organizations are looking to aggregate and share information to enable more precise analytic applications. This may also entail the moving data to the cloud for greater efficiencies such as hosting workloads for large clinical trials for complex genetic diseases. However, due to privacy risks and healthcare regulations, it is often impractical for healthcare organizations to share information or make the transition to cloud. Past solutions to either completely anonymize data or restrict access through stringent data use agreements have limited the utility of abundant and valuable patient data. Clinical research has been constrained due to the lack of data-sharing protocols resulting in diminishing learning from real-world data due to the lowering of sample sizes and data richness.

     

    For decades, industry has benefited from modern cryptography to protect sensitive data during transmission and in storage. However, it has been impossible to keep the data protected while being processed. What if you could begin to unlock the value of your sensitive data without decrypting it to preserve privacy?

     

    This session will explore IBM’s Fully Homomorphic Encryption (FHE) innovations. With FHE, the data never gets decrypted. The information is encoded in such a way that it remains encrypted all the time; when it’s being transmitted, when it’s in storage, and also during computation. The data stays cryptographically jumbled to preserve privacy while being processed so that even those handling the data cannot know the contents. So even if the data gets stolen or leaked, it will remain safely encrypted.

     

    During this session, we will introduce, and demonstrate, IBM’s AI SDK, a portfolio of capabilities that can be used to build secure analytics solutions and unlock the value stored in confidential data looking at:

     

    ·How third party or separate business can perform analytics on encrypted data without exposing the information.

    ·How to perform encrypted searches while concealing your search query and contents.

    ·How to train AI and machine learning models with sensitive data while preserving privacy and compliance.

    ·How to integrate FHE techniques into typical data science approaches

    This session will also look at how our FHE innovation enables the use of cloud-based architectures and supports our customers journey to hybrid cloud environments.

  • Speakers

    Dileep Rangan

    Business Development Director, Data & AI Expert Labs, IBM Asia-Pacific​

    leads IBM's Data & AI expert labs business development for Asia-Pacific. He is focused on helping clients address both immediate challenges and transform their businesses by modernizing their information architecture and putting AI to work.

    He has worked across industries including heavy industries in Korea and Japan, the financial sector, and the public sector on customer-facing and internal corporate use cases.

    Prior to joining IBM’s data and AI businesses he led a complex business transformation to account for a global FMGC, responsible for Asia, Africa, and the Middle-East. He has held leadership roles with IBM global procurement in Canada, Thailand, India, and Singapore directly supporting growth in the services business lines and driving value through 3rd party relationships. Dileep started his career in law with his own practice and then providing legal support for IBM's global procurement teams. Dileep has been based in Singapore since 2005.

    Sudesh Krishnamoorthy

    Technical Presales Architect, Data Science & AI Software, IBM Singapore

    is a Technical Architect of Data Science & AI Software for IBM Singapore. He helps clients explore and create cloud-based solutions that leverage data, analytics and artificial intelligence (AI) capabilities to deliver better decisions and outcomes.

     

    Sudesh has been at IBM for over 15 years and holds a master’s degree in Computer Science.

    Chan Chung Kit

    Technical Architect, Watson AI Centre of Competency, IBM ASEAN​

    is the technical leader and architect for the IBM Watson AI in ASEAN. He has been with IBM for more than 20 years and Watson AI since 2014. He ensures that the AI projects are solution and implemented based on customer’s business requirements and help to augment the customer business. He also ensures that the AI project has the correct data and corpus to train Watson AI and correct technical environment to deploy.

     

    Chung Kit has helped many major Watson customers such as NUS, DBS Singapore, Hong Leong Bank Malaysia, Hyundai Card Korea to successfully implement AI projects.

    John Buselli​

    IBM Business Development Executive, IBM Almaden Research Lab

    is a Business Development Executive for IBM Research currently focused on the development and delivery of confidential computing and data privacy innovations. Since joining IBM Research in January 2015, John has focused on cybersecurity, data governance, identity/blockchain and AI Analytic initiatives. He previously led a global team in IBM tasked with building an Information Governance/Compliance Practice within the IBM software organization. His career has been focused on establishing and expanding initial markets and operations for early-stage software firms including Princeton Softech (purchased by IBM) and KVS (acquired by Symantec) as well as senior leadership roles at Verity, Seer Technologies and Texas Instruments.

    Omri Soceanu

    AI Security Group Manager, IBM Haifa Research Lab

    is the head of the AI Security research group at IBM Research Haifa. He holds a B.Sc. and M.Sc. in Electrical Engineering from the Technion - Israel Institute of Technology. Before becoming the head of the AI Security group, Omri worked on different aspects of data security, employing machine learning techniques in a Big Data setting using state-of-the-art approaches. Omri has several years of hands-on experience working on embedded systems, cryptography, cyber-security, and machine learning algorithms.

  • Organizing Partners