This systematic review explores machine learning (ML) applications in surgical motion analysis using non-optical motion tracking systems (NOMTS), alone or with optical methods. It investigates objectives, experimental designs, model effectiveness, and future research directions….
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Amol Dalvi, VP of Product at Nerdio
Healthcare is navigating an era of unprecedented technological evolution while contending with rising cybersecurity threats and increasing demands on IT systems. Amid these challenges, hyperautomation emerges as a…
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What You Should Know:
– Predictive Oncology Inc. (NASDAQ: POAI), a leader in AI-driven drug discovery, announced its upcoming acquisition by Renovaro, Inc. (NASDAQ: RENB) in a strategic move aimed at accelerating innovation and improving…
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To support the continued development and marketing of safe and effective medical devices enhanced by artificial intelligence, the U.S. Food and Drug Administration will offer marketing submission recommendations, including the documentation and information needed…
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Bed capacity management is of critical importance to health systems, impacting patient care and safety, operational efficiency, system sustainability, and financial performance. Efforts to improve and streamline management often are isolated to regions within…
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Discover Your Core Competencies
Compared with other industries, healthcare has been perceived as lagging when it comes to adopting new technologies. But in recent years, it has really advanced in the areas of artificial intelligence…
What You Should Know:
– Certis Oncology Solutions, a translational science and emerging technology leader in preclinical oncology research, is pleased to announce the commercial launch of CertisOI Assistant™, an innovative chatbot tool designed to enhance…
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The Coalition for Health AI this past Friday unveiled news plans for how it would certify independent artificial intelligence assurance labs.The draft frameworks come as the group – comprising health system heavy-hitters such as…
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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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Machine learning and artificial intelligence (AI/ML) models in healthcare may exacerbate health biases. Regulatory oversight is critical in evaluating the safety and effectiveness of AI/ML devices in clinical settings. We conducted a scoping review…
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