From Species Identification to Empirical Therapy: A Machine Learning and Rule-Based Decision Support Framework for Antifungal Resistance Prediction in ICU Candida Infections.

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Title: From Species Identification to Empirical Therapy: A Machine Learning and Rule-Based Decision Support Framework for Antifungal Resistance Prediction in ICU Candida Infections.
Authors: Solomon MP; Department of Microbiology, Parasitology and Virology, Faculty of Nursing, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania.; Clinical Laboratory of Medical Microbiology, Marius Nasta Institute of Pneumology, 050159 Bucharest, Romania., Mahler B; Cardiothoracic Department, Faculty of Medicine, Carol Davila University of Medicine and Pharmacy, 020956 Bucharest, Romania.; Pneumology Department, Marius Nasta Institute of Pneumology, 050159 Bucharest, Romania., Ditu LM; Department of Botany and Microbiology, Faculty of Biology, University of Bucharest, 060101 Bucharest, Romania.; MICROGEN Research Centre, Faculty of Biology, University of Bucharest, 060101 Bucharest, Romania., Popescu O; National Reference Laboratory of Tuberculosis, Marius Nasta Institute of Pneumology, 050159 Bucharest, Romania., Zugravu CA; Department of Hygiene and Nutrition, Carol Davila University of Medicine and Pharmacy, 050463 Bucharest, Romania.; National Institute of Public Health, 050463 Bucharest, Romania., Manolescu LSC; Department of Microbiology, Parasitology and Virology, Faculty of Nursing, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania.; Clinical Laboratory of Medical Microbiology, Marius Nasta Institute of Pneumology, 050159 Bucharest, Romania.
Source: Medical sciences (Basel, Switzerland) [Med Sci (Basel)] 2026 Jun 15; Vol. 14 (2). Date of Electronic Publication: 2026 Jun 15.
Publication Type: Journal Article
Journal Info: Publisher: MDPI AG Country of Publication: Switzerland NLM ID: 101629322 Publication Model: Electronic Cited Medium: Internet ISSN: 2076-3271 (Electronic) Linking ISSN: 20763271 NLM ISO Abbreviation: Med Sci (Basel) Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2076-3271
DOI:10.3390/medsci14020319