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Purpose: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant opportunities in the diagnosis and management of glaucoma. This article explores the application of various DL models in enhancing OCT capabilities and addresses the challenges associated with their clinical implementation.

Methods: A review of articles utilizing DL models was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), autoencoders, and large language models (LLMs).

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Biofield Therapies Clinical Research Landscape: A Scoping Review and Interactive Evidence Map.

J Integr Complement Med

January 2025

Research Consultant to Subtle Energy Funders Collective, Warwick, New York, USA.

Biofield Therapies, with a historical lineage spanning millennia and continuing relevance in contemporary practices, have been used to address various health conditions and promote wellbeing. The scientific study and adoption of these therapies have been hindered by cultural challenges and institutional barriers. In addition, the current research landscape for Biofield Therapies is insufficiently documented.

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Measurable residual disease (MRD) is a powerful predictor of clinical outcomes in acute lymphoblastic leukemia (ALL). In addition to its clear prognostic importance, MRD information is increasingly used in clinical decision algorithms to guide therapeutic interventions. While it is well-established that achievement of MRD-negative remission is an important endpoint of ALL therapy, the prognostic and therapeutic implications of MRD in an individual patient are influenced by both disease-related factors (e.

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Limited research has examined the possible synergistic interrelationships between serious bacterial infections (SBIs) of the heart (i.e., endocarditis), bone, spine, brain, or joints (e.

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