The ability to detect errors during cognitive performance is compromised in older age and in a range of clinical populations. This study was designed to assess the effects of transcranial direct current stimulation (tDCS) on error awareness in healthy older human adults. tDCS was applied over DLPFC while subjects performed a computerized test of error awareness. The influence of current polarity (anodal vs cathodal) and electrode location (left vs right hemisphere) was tested in a series of separate single-blind, Sham-controlled crossover trials, each including 24 healthy older adults (age 65-86 years). Anodal tDCS over right DLPFC was associated with a significant increase in the proportion of performance errors that were consciously detected, and this result was recapitulated in a separate replication experiment. No such improvements were observed when the homologous contralateral area was stimulated. The present study provides novel evidence for a causal role of right DLPFC regions in subserving error awareness and marks an important step toward developing tDCS as a tool for remediating the performance-monitoring deficits that afflict a broad range of populations.
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http://dx.doi.org/10.1523/JNEUROSCI.5308-13.2014 | DOI Listing |
Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope into the joint through a small incision, during which surgeons navigate and operate largely by relying on their visual assessment through the arthroscope. However, the arthroscope's restricted field of view and lack of depth perception pose challenges in navigating complex articular structures and achieving surgical precision during procedures.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
RPTU Kaiserslautern-Landau, Kaiserslautern, Germany.
The advent of in-memory computing has introduced a new paradigm of computation, which offers significant improvements in terms of latency and power consumption for emerging embedded AI accelerators. Nevertheless, the effect of the hardware variations and non-idealities of the emerging memory technologies may significantly compromise the accuracy of inferred neural networks and result in malfunctions in safety-critical applications. This article addresses the issue from three different perspectives.
View Article and Find Full Text PDFIowa Orthop J
January 2025
NYU Langone Orthopedic Hospital, New York, New York, USA.
Background: Optimal management of post-operative pain is a critical component of orthopedic surgical care. There is a heightened awareness of narcotic prescribing habits given the current "opioid epidemic." The lack of standardized protocols has led to increased errors, delayed access to prescribed medications, and excessive narcotic prescribing.
View Article and Find Full Text PDFEur J Oncol Nurs
January 2025
The Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong, China.
Purpose: To explore how regional economic levels moderate the relationships between cancer-related financial toxicity (FT) and its associated risk factors.
Methods: A secondary analysis was conducted using data from a cross-sectional survey of 1208 adult patients with cancer, conducted in six tertiary and six secondary hospitals across three Chinese provinces from February to October 2022. The interactions between the regional economic level-categorised as high- or low-/middle-income based on the gross domestic product per capita- and 13 previously identified risk factors for FT were examined via moderation analysis using the PROCESS macro for SPSS software.
Ensuring trustworthiness is fundamental to the development of artificial intelligence (AI) that is considered societally responsible, particularly in cancer diagnostics, where a misdiagnosis can have dire consequences. Current digital pathology AI models lack systematic solutions to address trustworthiness concerns arising from model limitations and data discrepancies between model deployment and development environments. To address this issue, we developed TRUECAM, a framework designed to ensure both data and model trustworthiness in non-small cell lung cancer subtyping with whole-slide images.
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