Results 11 to 20 of about 634 (150)

Distorted learning from local metacognition supports transdiagnostic underconfidence [PDF]

Nature Communications, 2023
Individuals experiencing symptoms of anxiety and depression have been shown to exhibit persistent underconfidence. The origin of such metacognitive biases presents a puzzle, given that individuals should be able to learn appropriate levels of confidence ...
Sucharit Katyal, Quentin JM Huys, Raymond J. Dolan, Stephen M. Fleming   +3 more
doaj   +6 more sources

Gender and anxiety reveal distinct computational sources of underconfidence. [PDF]

Psychol Med
Abstract Background Confidence exhibits systematic individual differences across mental health, gender, and age. However, it remains unknown whether these distinct sources of metacognitive bias have common or distinct computational origins.
Katyal S, Fleming SM.
europepmc   +3 more sources

Sensitivity of Bayesian Networks to Noise in Their Parameters [PDF]

Entropy
There is a widely spread belief in the Bayesian network (BN) community that the overall accuracy of results of BN inference is not too sensitive to the precision of their parameters.
Agnieszka Onisko, Marek J. Druzdzel
doaj   +2 more sources

Drops in confidence precede symptoms of obsessive-compulsive disorder [PDF]

Nature Communications
Mental health symptoms, like those in obsessive-compulsive disorder, show pronounced fluctuations over time. However, little is known about the underlying factors driving these fluctuations.
A. A. Marzuki, L. A. Kosina, L. Dome, S. R. C. Hewitt, T. U. Hauser   +4 more
doaj   +2 more sources

Electrocardiogram Abnormality Classification From Summary Statistics With Patient-Level Validation and Process-Focused Evaluation. [PDF]

Ann Noninvasive Electrocardiol
Patient‐level validation in ECG abnormality classification demonstrates that detailed evaluation (including monotonic decline patterns, learning convergence, and precision‐recall calibration across partitions) is vital for clinical deployment. Aggregate accuracy metrics alone mask critical generalization instabilities, highlighting the need for process‐
Hong S, Hartnett C, Ruane M, Tagliarino J, Nizich M, Toma M.   +5 more
europepmc   +2 more sources

No gender difference in cardiac interoceptive accuracy: Potential psychophysiological contributors in heartbeat counting task [PDF]

BMC Psychology
Gender differences in interoceptive awareness—awareness of internal bodily signals such as heartbeat perception—have been suggested, with some findings indicating behaviourally reduced but subjectively enhanced awareness in women, though these findings ...
Yusuke Haruki, Kei Kaneko, Kenji Ogawa
doaj   +2 more sources

Enhancing integration of administrative databases in South Africa's HIV program: Validation of record linkage using non-representative gold standard [PDF]

International Journal of Population Data Science
Introduction Linked administrative data are widely used in epidemiology to capture patient data across multiple databases. Linkage error rates, critical to measure linkage performance, are rarely reported due to difficulty in obtaining representative ...
Evelyn Lauren, Dickman Gareta, Khumbo Shumba, Dorina Onoya, Jacob Bor   +4 more
doaj   +2 more sources

Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches. [PDF]

Chemistry
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Garain BC, Pinheiro M, Bispo MO, Barbatti M.   +3 more
europepmc   +2 more sources

Machine learning prediction of PICC-associated thrombotic complications in critically ill patients [PDF]

BMC Medical Informatics and Decision Making
Background Peripherally inserted central catheters (PICCs) are widely used vascular access devices in intensive care, yet thrombotic complications remain a significant clinical concern.
Liyan Xia, Hailan Jiang, Yanfei Zhang, Jiahui Guo, Mengying Sun, Haitao Wu, Yang Cui, Yongjie Wang   +7 more
doaj   +2 more sources

Metacognitive biases in anxiety-depression and compulsivity extend across perception and memory. [PDF]

PLOS Mental Health
Metacognitive biases are characteristic of common mental health disorders like depression and obsessive-compulsive disorder (OCD). However, recent transdiagnostic approaches consistently contradict traditional clinical studies, with overconfidence in ...
Tricia X F Seow, Stephen M Fleming, Tobias U Hauser   +2 more
doaj   +2 more sources