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Articles by Sara Moccia
Domain-specific ControlNet training for neonatal pose-conditioned image generation
Abstract Several automatic approaches have been proposed to analyse spontaneous movements in infants, but translation to clinical practice remains limited by the scarcity of neonatal data, especially in preterm populations. Generative models can help expand existing datasets, yet current solutions—such as generative adversarial networks or diffusion models—often fail to preserve anatomical and pose consistency.
Advancements in Multilingual Biomedical Natural Language Processing: exploring Large Language Models for Named Entity Recognition and Linking
The authors have declared no competing interest. I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Ethics Committee of Erasmus University Medical Center waived ethical approval for this work.
"Non però stimo, ch’esser ci debba inviolabil legge": Le canzoni di Minturno tra teoria e prassi metrica
Ayuda Buscar en la ayuda Buscar en la ayuda
FUORI DAL GIRO – Concorso su TikTok per sensibilizzare al contrasto delle dipendenze - portale giovani
FUORI DAL GIRO – Concorso su TikTok per sensibilizzare al contrasto delle dipendenze Aggiornato a: 11 Aprile 2025 FUORI DAL GIRO – Il concorso TikTok per chi ha qualcosa da dire! Hai tra i 14 e i 17 anni e ti piace creare video su TikTok ?
Il "Repertorio Digitale della Canzone Italiana". Forme e funzioni del metro nel secondo Cinquecento
Ayuda Buscar en la ayuda Buscar en la ayuda Il «Repertorio Digitale della Canzone Italiana». Forme e funzioni del metro nel secondo Cinquecento Autores: Sara Moccia Localización: Stilistica e metrica italiana, ISSN 1591-6693, Nº. 23, 2023, págs. 153-174 Idioma: italiano Títulos paralelos: «Repertorio Digitale Della Canzone Italiana».
Tree-based survival analysis improves mortality prediction in cardiac surgery
Introduction The extraordinary physiologically stress of cardiac surgery carries a high risk of adverse postoperative outcomes (1). An important component of surgical decision-making is determining which patients will ultimately benefit after overcoming the initial insult of surgery. Overall survival is an important, albeit complex, metric for understanding the overall benefit of a surgery (2, 3).
Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases
1. Introduction Successful treatment of rheumatic diseases affecting the hands depends on an accurate and fast diagnosis in patients presenting with hand pain (1). Fluorescence optical imaging (FOI) has been used to study a number of rheumatic diseases, including, for example, rheumatoid arthritis (RA) (2–4), osteoarthritis (OA) (4, 5), connective tissue diseases (CTD) (6, 7), and others (8, 9).
Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging
Introduction This paper focuses on the procedures, including data and training, needed for convolutional neural net learning to segment the brain cavity within structural magnetic resonance imaging (MRI). Convolutional neural nets (CNNs) (Bengio, 2009) are particularly well suited for image analysis and have recently been used in a variety of applications for medical image processing (Litjens et al., 2017; Zhang et al., 2017; Lundervold and Lundervold, 2019).
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