Effective hemodynamic management in the intensive care unit requires individualized targets that adapt to dynamic clinical conditions. We developed Dynamic Cohort Ensemble Learning (DynaCEL), a real-time framework that recommends personalized heart rate and systolic…
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In healthcare, federated learning (FL) is emerging as a methodology to enable the analysis of large and disparate datasets while allowing custodians to retain sovereignty. While FL minimises data-sharing challenges, concerns surrounding ethics, privacy,…
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Lymph node micro-metastasis represents the initial stage of breast cancer spread or metastasis. However, the limited size of these hidden lesions restricts dataset expansion, presenting a significant challenge for manual examination and conventional deep…
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What You Should Know:
– Certara, a global leader in model-informed drug development, today announced an expanded collaboration with Merck, known as MSD outside of the United States and Canada.
– The strategic agreement will see…
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Several open-source oral-maxillofacial imaging datasets have been created but their characteristics, ethical clearance, and licensing for reuse remain unclear. This study aimed to systematically identify these datasets and investigate their characteristics, ethical approvals, and…
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Government entities overseeing medication access in New Zealand have been planning their adoption of AI assistants and tools to speed up processes and support decision-making.The New Zealand Medicines and Medical Devices Safety Authority (Medsafe)…
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Low-income populations have disproportionately low completion of recommended healthcare services, from missed vaccinations to cancer screenings. While machine learning models help identify high-risk patients for targeted treatment, they have rarely been evaluated for quality…
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Fundus fluorescein angiography (FFA) is the gold standard for diagnosing chorioretinal diseases, but its interpretation requires significant expertise and time. Despite generative AI’s enormous potential in medical report generation, automatic FFA interpretation lacks robust…
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Immunohistochemistry (IHC) is crucial for the clinical categorisation of breast cancer cases. Deep generative models may offer a cost-effective alternative by virtually generating IHC images from hematoxylin and eosin samples. This review explores the…
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Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always…
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