Publications by authors named "Sara Manzoni"
hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction.
Front Neuroinform
December 2024
Introduction: Modeling multi-channel electroencephalographic (EEG) time-series is a challenging tasks, even for the most recent deep learning approaches. Particularly, in this work, we targeted our efforts to the high-fidelity reconstruction of this type of data, as this is of key relevance for several applications such as classification, anomaly detection, automatic labeling, and brain-computer interfaces.
Methods: We analyzed the most recent works finding that high-fidelity reconstruction is seriously challenged by the complex dynamics of the EEG signals and the large inter-subject variability.
Article Synopsis
- - A 6-year-old spayed cat had a nasal dermoid sinus cyst removed, which also involved reconstructing a defect in the nasal bone using a fascia lata graft.
- - The surgery was successful, with no respiratory issues or complications noted during follow-up at 2 weeks, 2 months, and 12 months.
- - This case is the first of its kind to demonstrate the effectiveness of fascia lata grafts for repairing nasal bone defects after cyst removal in cats, highlighting its low cost and good outcomes.
Article Synopsis
- Polycythemia vera (PV) is a type of blood cancer where the bone marrow produces too many blood cells, mostly due to a mutation in the JAK2 gene.
- Givinostat, a drug that inhibits cell growth related to JAK2, has shown positive results in earlier studies, prompting a long-term study on its effects in patients with PV.
- Over a 4-year follow-up of patients, givinostat was found to have a good safety profile, with only 10% experiencing serious side effects, while more than 80% showed positive treatment responses.
Objective: To review systematically community-based primary care interventions for epilepsy in low- and middle-income countries to rationalize approaches and outcome measures in relation to epilepsy care in these countries.
Methods: A systematic search of PubMed, EMBASE, Global Index Medicus, CINAHL, and Web of Science was undertaken to identify trials and implementation of provision of antiseizure medications, adherence reinforcement, and/or health care provider or community education in community-based samples of epilepsy. Data on populations addressed, interventions, and outcomes were extracted from eligible articles.
Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial.
Comput Methods Programs Biomed
March 2020
Background: The literature shows the effectiveness of music listening, but which factors and what types of music produce therapeutic effects, as well as how music therapists can select music, remain unclear. Here, we present a study to establish the main predictive factors of music listening's relaxation effects using machine learning methods.
Methods: Three hundred and twenty healthy participants were evenly distributed by age, education level, presence of musical training, and sex.
Patients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming to correct any differentiation between VS and MCS are essential for the characterization of an adequate treatment and an effective prognosis.
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