The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated…
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Neonatal seizures require urgent treatment, but often go undetected without expert EEG monitoring. We have developed and validated a seizure detection model using retrospective EEG data from 332 neonates. A convolutional neural network was…
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Label noise is a common and important issue that would affect the model’s performance in artificial intelligence. This study assessed the effectiveness and potential risks of automated label cleaning using an open-source framework, Cleanlab,…
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The U.S. Department of Defense’s Chief Digital and Artificial Intelligence Office and Humane Intelligence, a technology nonprofit, has announced the conclusion of the agency’s Crowdsourced Artificial Intelligence Red-Teaming Assurance Program pilot, which is focused…
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Artificial Intelligence technologies have the potential to improve multiple aspects of healthcare research, diagnosis and care delivery, according to a Bipartisan House Task Force Report on Artificial Intelligence.The report highlights America’s leadership in its…
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A set of internationally-agreed recommendations has been published with the aim of reducing the risk of potential bias in AI for healthcare technologies.
The guidelines from the STANDING Together initiative, published The Lancet Digital Health…
Automated clinical coding (ACC) has emerged as a promising alternative to manual coding. This study proposes a novel human-in-the-loop (HITL) framework, CliniCoCo. Using deep learning capacities, CliniCoCo focuses on how such ACC systems and…
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Large Language Models (LLMs) have shown promise in clinical applications through prompt engineering, allowing flexible clinical predictions. However, they struggle to produce reliable prediction probabilities, which are crucial for transparency and decision-making. While explicit…
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Artificial intelligence promises to revolutionize mental health care, but small dataset sizes and lack of robust methods raise concerns about result generalizability. To provide insights on minimal necessary data set sizes, we explore domain-specific…
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During his tenure as head of the Portuguese Digital Health Agency between 2013 and 2020, Henrique Martins was responsible for advancing the nation’s eHealth strategy, including projects such as the health information sharing platform…
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