Demystifying deep learning: An accessible introduction to neural networks in health research and epidemiology

[Adobe Stock]

As machine learning and deep learning technologies advance thanks to advances in computation, algorithms and data availability, the possibilities of the technology continue to expand in medicine. While these AI-driven approaches have real potential, such systems demand large volumes of representative data, careful privacy and security scrutiny and thoughtful long-term strategic planning. In this Q&A, Kathryn Rough, associate director of the Center for Advanced Evidence Generation at IQVIA, discusses the impact of deep learning on healthcare delivery and recommends steps to take during the design, training, evaluation and deployment phases to increase the likelihood that these models will be safe, effective and ethical when trained on real-world health data. Rough also explores the role of epidemiologists in evaluating these technologies as part of multidisciplinary teams and provides advice for health…
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9 tips for implementing AI in medical devices from a Medtronic executive

Patients and healthcare providers remain at the core of successful AI implementations in medtech. [piai/Adobe Stock]

It seems like artificial intelligence (AI) is ubiquitous in the healthcare landscape, but the technology remains nascent in the industry. Technologies ranging from machine learning to natural language processing and beyond promise to help make diagnoses and treatment more precise, efficient, and personalized.

But the allure of AI can sometimes overshadow the central goal of addressing tangible clinical problems.

During his talk at DeviceTalks West, Ha Hong, chief AI officer at Medtronic Endoscopy, underscored the importance of putting patients and healthcare providers at the forefront when incorporating AI into medical devices.

With a plethora of AI tools at our disposal — many of which are increasingly user-friendly — the onus is on us to wield them responsibly. Below, you’ll find …

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Natalizumab and PML: The complex dance of benefit and risk for MS

MRI scan of a PML patient displaying prominent brain lesions (indicated by white signal). [Image credit: Daniel S. Reich, National Institute of Neurological Disorders and Stroke (NINDS)]

Biogen’s Tysabri (natalizumab), the first humanized monoclonal antibody for multiple sclerosis (MS), sparked optimism among MS patients following its FDA approval in 2004. The drug offered significant benefits, reducing relapses for patients resistant to other treatments. This was a significant milestone in the treatment of MS, but the journey of natalizumab and PML soon took a concerning turn.

Within a year, alarming reports surfaced: A number of patients were developing progressive multifocal leukoencephalopathy (PML), a rare and often fatal brain infection. The suspected culprit? Natalizumab’s immunomodulatory effect, which suppressed the immune cells fighting the JC (John Cunningham) virus…

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