The COVID-19 pandemic has challenged the current paradigm of clinical and community-based disease detection. We present a multimodal wearable sensor system paired with a two-minute, movement-based activity sequence that successfully captures a snapshot of…
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Deep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications. However, recent research highlights a performance disparity in these algorithms when applied to specific subgroups, such as exhibiting poorer predictive…
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This randomized clinical trial evaluated the effectiveness of short, digital interventions in improving physical activity and pain for individuals with knee osteoarthritis. We compared a digital mindset intervention, focusing on adaptive mindsets (e.g., osteoarthritis…
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Robust data privacy regulations hinder the exchange of healthcare data among institutions, crucial for global insights and developing generalised clinical models. Federated learning (FL) is ideal for training global models using datasets from different…
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Abdominal aortic aneurysm (AAA) often remains undetected until rupture due to limited access to diagnostic ultrasound. This trial evaluated a deep learning (DL) algorithm to guide AAA screening by novice nurses with no prior…
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In multicentric studies, data sharing between institutions might negatively impact patient privacy or data security. An alternative is federated analysis by secure multiparty computation. This pilot study demonstrates an architecture and implementation addressing both…
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Wearables offer a promising solution for enhancing remote monitoring (RM) of heart failure (HF) patients by tracking key physiological parameters. Despite their potential, their clinical integration faces challenges due to the lack of rigorous…
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Cognitive symptoms are prevalent across neuropsychiatric disorders, increase distress and impair quality of life. Self-guided digital interventions offer accessibility, scalability, and may overcome the research-to-practice treatment gap. Seventy-six trials with 5214 participants were identified….
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On-scene resuscitation time is associated with out-of-hospital cardiac arrest (OHCA) outcomes. We developed and validated reinforcement learning models for individualized on-scene resuscitation times, leveraging nationwide Korean data. Adult OHCA patients with a medical cause…
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What You Should Know:
– The Digital Medicine Society (DiMe) is launching a new collaboration with Google and Mayo Clinic to address the critical need for best practices and implementation strategies for artificial intelligence (AI)…
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