Workshop-rp
Description

PURPOSE: Over the last decade, the volume and diversity of imaging, genetic, and biochemical data has been growing exponentially. This phenomenon paves the way to precision medicine, which aims to improve human health by accounting for individual variations in genes, environment and lifestyle in both disease treatment and prevention strategies. To maximize the benefits from this big data revolution and more efficiently tailor prevention, diagnosis and treatment strategy, the healthcare industry has started to adopt new data analysis techniques. Thanks to concurrent advances in computer power and theoretical knowledge, artificial intelligence (AI) is now becoming the backbone technology for many medical devices. Through practical examples, this interactive workshop aims to discuss the implications of this new AI-backed medical device category for the patient, payer, device and drug developer.

DESCRIPTION: First, the concept of AI-backed precision medicine will be introduced, along with likely advantages and challenges for the healthcare ecosystem in terms of clinical, patient and reimbursement decision-making. Second, three real-world examples will be presented where “intelligent” (or AI-backed) medical devices received a positive Health Technology Assessment or are seeking reimbursement approval. Each device uses a specific type of data source and artificial intelligence technique. For instance, the analysis of imaging data through deep neural networks brings superior accuracy in diagnosing iron overload in cancer survivors whereas cerebrospinal biomarkers analyzed through bootstrap aggregating techniques can be used to prompt the management of Alzheimer Disease patients and avoid inappropriate treatments of patients with false negative diagnoses. Along with a brief background, we will discuss how the superior accuracy and lack of interpretability of “intelligent” devices drive clinical and economic value. Finally, the workshop attendees will be asked to share their view and personal experience on the clinical integration and reimbursement of “intelligent” medical devices.

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