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| http://dx.doi.org/10.3389/fchem.2022.1127842 | DOI Listing |
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Haemodynamic profiling: when AI tells us what we already know.
Br J Anaesth
February 2025
Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Parma, Italy.
Machine learning (ML) algorithms hold significant potential for extracting valuable clinical information from big data, surpassing the processing capabilities of the human brain. However, it would be naïve to believe that ML algorithms can consistently transform data into actionable insights. Clinical studies suggest that in some instances, they tell clinicians what they already know or can plainly see.
View Article and Find Full Text PDFEditorial: Novel technologies applied to flavoromics and sensory evaluation of foods.
Front Nutr
January 2025
Department of Food and Human Nutritional Sciences, Faculty of Agriculture and Food Sciences, University of Manitoba, Winnipeg, MB, Canada.
Shaping Future Medicinal Chemists: Perspectives from European Schools of Pharmacy within the GPA Network.
J Med Chem
January 2025
Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CiQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.
Deep Learning Superresolution for Simultaneous Multislice Parallel Imaging-Accelerated Knee MRI Using Arthroscopy Validation.
Radiology
January 2025
From the Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016 (S.S.W., J.V., R.K., E.H.P., J.F.); Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, University Hospital Tübingen, Tübingen, Germany (S.S.W.); Department of Radiology, University Hospital Basel, Basel, Switzerland (J.V.); Department of Radiology, Hospital do Coraçao, São Paulo, Brazil (T.C.R.); Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), London, United Kingdom (D.D.); Department of Radiology, Balgrist University Hospital, Zurich, Switzerland (B.F.); Department of Radiology, Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Research Institute of Clinical Medicine of Jeonbuk National University, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Medscanlagos Radiology, Cabo Frio, Brazil (A.S.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Siemens Healthineers AG, Erlangen, Germany (I.B.); and Siemens Medical Solutions USA, Malvern, Pa (G.K.).
Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (SMSx2) twofold-parallel-imaging (PIx2)-accelerated DL superresolution MRI in the knee against conventional SMSx2-PIx2-accelerated MRI using arthroscopy as the reference standard. Materials and Methods Adults with painful knee conditions were prospectively enrolled from December 2021 to October 2022.
View Article and Find Full Text PDFidentification through bronchoscope in intensive care unit - a retrospective, databased cohort study.
Front Cell Infect Microbiol
January 2025
Department of Thoracic Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Introduction: Invasive pulmonary aspergillosis (IPA) increases the risk of mortality of critically ill patients. Diagnostic criteria specifically targeting patients in intensive care units(ICUs) have been developed to improve diagnostic sensitivity. This study investigated health outcomes among patients in ICUs with Aspergillus isolates identified using bronchoscopy.
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