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Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study.
JMIR Form Res
January 2025
Northwestern Medicine, Chicago, IL, United States.
Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
Diagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.
JMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
Response Theory via Generative Score Modeling.
Phys Rev Lett
December 2024
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.
View Article and Find Full Text PDFPrecise Measurement of the e^{+}e^{-}→D_{s}^{+}D_{s}^{-} Cross Section at Center-of-Mass Energies from Threshold to 4.95 GeV.
Phys Rev Lett
December 2024
State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China.
Using the e^{+}e^{-} collision data collected with the BESIII detector operating at the BEPCII collider, at center-of-mass energies from the threshold to 4.95 GeV, we present precise measurements of the cross section for the process e^{+}e^{-}→D_{s}^{+}D_{s}^{-} using a single-tag method. The resulting cross section line shape exhibits several new structures, thereby offering an input for a future coupled-channel analysis and model tests, which are critical to understand vector charmonium-like states with masses between 4 and 5 GeV.
View Article and Find Full Text PDFNH-MIL-125(Ti) and its functional nanomaterials - a versatile platform in the photocatalytic arena.
Nanoscale
January 2025
Centre for Nano Science and Nano Technology, S 'O' A (Deemed to be University), Bhubaneswar-751 030, Odisha, India.
Titanium (Ti)-based MOFs are promising materials known for their porosity, stability, diverse valence states, and a lower conduction band (CB) than Zr-MOFs. These features support stable ligand-to-metal charge transfer (LMCT) transitions under photoirradiation, enhancing photocatalytic performance. However, Ti-MOF structures remain a challenge owing to the highly volatile and hydrophilic nature of ionic Ti precursors.
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