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| http://dx.doi.org/10.3389/fneur.2021.778765 | DOI Listing |
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Editorial: 21st meeting of the international council for near infrared spectroscopy - NIR 2023.
Spectrochim Acta A Mol Biomol Spectrosc
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Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Austria. Electronic address:
NIR 2023, or the 21st meeting of The International Council for Near Infrared Spectroscopy (ICNIRS), held in Innsbruck, Austria, in August 2023, was a significant event for the NIR spectroscopy community, bringing together 386 participants from 37 countries. This editorial introduces the Special Issue of Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, featuring nearly 30 articles that represent the topics from the conference. Like the NIR 2023 event itself, this collection highlights advancements in NIR spectroscopy, including fundamental research, instrumentation, and applications.
View Article and Find Full Text PDFArtificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture: a critical review.
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Clinical Scientific Computing, Guy's and St Thomas' NHS Foundation Trust, London, UK.
This paper discusses the current literature surrounding the potential use of artificial intelligence and machine learning models in the diagnosis of acute obvious and occult scaphoid fractures. Current studies have notable methodological flaws and are at high risk of bias, precluding meaningful comparisons with clinician performance (the current reference standard). Specific areas should be addressed in future studies to help advance the meaningful and clinical use of artificial intelligence for radiograph interpretation.
View Article and Find Full Text PDFLearning and fine-tuning a generic value-selection heuristic inside a constraint programming solver.
Constraints
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Polytechnique Montréal, Montreal, Canada.
Constraint programming is known for being an efficient approach to solving combinatorial problems. Important design choices in a solver are the , designed to lead the search to the best solutions in a minimum amount of time. However, developing these heuristics is a time-consuming process that requires problem-specific expertise.
View Article and Find Full Text PDFFostering effective hybrid human-LLM reasoning and decision making.
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Center for Mind/Brain Sciences, University of Trento, Trento, Italy.
The impressive performance of modern Large Language Models (LLMs) across a wide range of tasks, along with their often non-trivial errors, has garnered unprecedented attention regarding the potential of AI and its impact on everyday life. While considerable effort has been and continues to be dedicated to overcoming the limitations of current models, the potentials and risks of human-LLM collaboration remain largely underexplored. In this perspective, we argue that enhancing the focus on human-LLM interaction should be a primary target for future LLM research.
View Article and Find Full Text PDFAIding, Not Replacing, Clinicians: A Machine-Based Learning Approach to Predict Successful Outcomes in Transcatheter Tricuspid Valve Interventions.
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Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. Electronic address:
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