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Large Language Models lack essential metacognition for reliable medical reasoning.
Nat Commun
January 2025
Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium.
Large Language Models have demonstrated expert-level accuracy on medical board examinations, suggesting potential for clinical decision support systems. However, their metacognitive abilities, crucial for medical decision-making, remain largely unexplored. To address this gap, we developed MetaMedQA, a benchmark incorporating confidence scores and metacognitive tasks into multiple-choice medical questions.
View Article and Find Full Text PDFBeyond arrhythmias in the ECG: Is there any correlation between QT interval and stroke subtype and severity?
J Clin Neurosci
January 2025
Comprehensive Centre for Stroke Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala 695011, India. Electronic address:
Background: The QT interval in ECG is susceptible to autonomic fluctuations, a known occurrence in acute ischemic stroke (AIS). Previous research has highlighted QT interval changes between ischemic and haemorrhagic strokes. However, there is scarce literature on the differential effect of AIS subtypes on QT interval.
View Article and Find Full Text PDFProtonation effects in protein-ligand complexes - a case study of endothiapepsin and pepstatin A with computational and experimental methods.
ChemMedChem
January 2025
Crystals First GmbH, -, GERMANY.
Protonation states serve as an essential molecular recognition motif for biological processes. Their correct consideration is key to successful drug design campaigns, since chemoinformatic tools usually deal with default protonation states of ligands and proteins and miss atypical protonation states. The protonation pattern for the Endothiapepsin/PepstatinA (EP/pepA) complex is investigated using different dry lab and wet lab techniques.
View Article and Find Full Text PDFNew Library-Based Methods for Nontargeted Compound Identification by GC-EI-MS.
J Am Soc Mass Spectrom
January 2025
Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8362, United States.
While gas chromatography mass spectrometry (GC-MS) has long been used to identify compounds in complex mixtures, this process is often subjective and time-consuming and leaves a large fraction of seemingly good-quality spectra unidentified. In this work, we describe a set of new mass spectral library-based methods to assist compound identification in complex mixtures. These methods employ mass spectral uniqueness and compound ubiquity of library entries alongside noise reduction and automated comparison of retention indices to library compounds.
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