Alessia Sarica

Alessia Sarica
Universita' degli Studi "Magna Græcia" di Catanzaro | Università Magna Græcia di Catanzaro · Department of Medical and Surgical Sciences

Ph.D in Biomedical and Computer Science Engineering
Quantification of similarity between feature importance rankings https://link.springer.com/chapter/10.1007/978-3-031-150

About

68
Publications
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Introduction
Assistant Professor of Applied Medical Technology and Methodology, Neuroscience Research Center, Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, Italy. Ph.D. in Biomedical and Computer Engineering.
Additional affiliations
June 2012 - March 2015
Universita' degli Studi "Magna Græcia" di Catanzaro
Position
  • Engineer

Publications

Publications (68)
Article
Full-text available
Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been successfully applied for reducing high dimensional and multi-source data in many scientific realms....
Chapter
Although automatic prediction of Alzheimer’s disease (AD) from Magnetic Resonance Imaging (MRI) showed excellent performance, Machine Learning (ML) algorithms often provide high accuracy at the expense of interpretability of findings. Indeed, building ML models that can be understandable has fundamental importance in clinical context, especially fo...
Article
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In the last decade, Machine Learning (ML) has indisputably had a pervasive application in healthcare and biomedical applications [...]
Article
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Scans without evidence of dopaminergic deficit (SWEDD) refers to patients who mimics motor and non-motor symptoms of Parkinson's disease (PD) but showing integrity of dopaminergic system. For this reason, the differential diagnosis between SWEDD and PD patients is often not possible in absence of dopamine imaging. Machine Learning (ML) showed optim...
Article
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Feature importance is one of the most common explanations provided by Machine Learning (ML). However, different classification algorithms or different training sets could produce different rankings of predictive features. Thus, the quantification of differences between feature importance is crucial for assessing model trustworthiness. Rank-biased O...
Article
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Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accu...
Article
Introduction Progressive supranuclear palsy (PSP) and idiopathic normal pressure hydrocephalus (iNPH) share several clinical and radiological features, making the differential diagnosis challenging. In this study, we aimed to differentiate between these two diseases using a machine learning approach based on cortical thickness and volumetric data....
Article
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The clinical differential diagnosis between Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certaint...
Article
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Background Imaging studies investigating cerebellar gray matter (GM) in essential tremor (ET) showed conflicting results. Moreover, no large study explored the cerebellum in ET patients with resting tremor (rET), a syndrome showing enhanced blink reflex recovery cycle (BRrc). Objective To investigate cerebellar GM in ET and rET patients using voxe...
Article
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Background Approximatively, 10% of patients initially diagnosed with Parkinson’s disease (PD) show preserved presynaptic dopaminergic function in the nigrostriatal pathway on DAT-SPECT imaging. This syndrome is not compatible with PD diagnosis, and is known as scans without evidence of dopaminergic deficit (SWEDD). Objective To investigate structu...
Article
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The idea that individuals tend to choose a romantic partner following similarities on personality traits has always attracted much attention in the psychological literature, although results were controversial. We conducted a new data analysis approach to personality traits of 235 newlywed couples. Univariate analysis revealed that a neurotic husba...
Preprint
Full-text available
Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accu...
Article
Full-text available
Background Microstructural alterations of corticospinal tract (CST) have been found in idiopathic normal pressure hydrocephalus (iNPH). No study, however, investigated the effect of ventricular dilatation on CST in Progressive Supranuclear Palsy (PSP). Objective The aim of this study was to investigate CST diffusion profile in a large cohort of PS...
Article
Background Progressive supranuclear palsy (PSP) patients can show ventricular enlargement mimicking normal pressure hydrocephalus (NPH). The aim of this study was to distinguish PSP patients with marked ventricular dilatation (PSP-vd) from those with normal ventricular system and to evaluate the coexistence of NPH in PSP-vd patients.Methods One hun...
Article
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The COVID-19 outbreak has dramatically impacted on socioeconomic structure, individual freedom, general wellbeing, psychological health and sexuality. Indeed, social distancing, home confinement and the fear of contagion have reduced the possibility of romantic encounters thus influencing sexual activity, desire and behavior and, consequently, modi...
Article
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Cluster analysis is widely applied in the neuropsychological field for exploring patterns in cognitive profiles, but traditional hierarchical and non-hierarchical approaches could be often poorly effective or even inapplicable on certain type of data. Moreover, these traditional approaches need the initial specification of the number of clusters, b...
Article
Background Resting-state-fMRI is a technique used to explore the functional brain architecture in term of brain networks and their interactions. However, the robustness of Resting-state-fMRI analysis is negatively affected by physiological noise caused by subject head motion. The aim of our study was to provide new knowledge about the effect of nor...
Article
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Progressive supranuclear palsy (PSP) is a rare, rapidly progressive neurodegenerative disease. Richardson’s syndrome (PSP-RS) and predominant parkinsonism (PSP-P) are characterized by wide range of cognitive and behavioural disturbances, but these variants show similar cognitive pattern of alterations, leading difficult differential diagnosis. For...
Conference Paper
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Synopsis We present results from IronTract, the first challenge to evaluate tractography on the two-shell diffusion scheme of the Human Connectome Project (HCP). Accuracy was evaluated by comparison to tracer injections in the same macaque brains as the diffusion data. Training and validation datasets involved different injection sites. We observed...
Article
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Aim: The aim of this study was to evaluate the corticospinal tract (CST) diffusion profile in pure lower motor neuron disease (pLMND) patients who at baseline did not show any clinical or electrophysiological involvement of upper motor neurons (UMN), and in amyotrophic lateral sclerosis (ALS) patients. Materials and methods: Fifteen ALS patients...
Article
Background Idiopathic normal pressure hydrocephalus and PSP share several clinical and radiological features, making differential diagnosis, at times, challenging. Objectives To differentiate idiopathic normal pressure hydrocephalus from PSP using MR volumetric and linear measurements. Methods Twenty‐seven idiopathic normal pressure hydrocephalus...
Article
Full-text available
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Article
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Machine Learning application on clinical data in order to support diagnosis and prognostic evaluation arouses growing interest in scientific community. However, choice of right algorithm to use was fundamental to perform reliable and robust classification. Our study aimed to explore if different kinds of Machine Learning technique could be effectiv...
Article
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Objective To evaluate whether increased cerebrospinal fluid (CSF) pressure causes alteration of periventricular white matter (WM) microstructure in patients with idiopathic intracranial hypertension (IIH). Methods In a prospective study, patients with refractory chronic headache with and without IIH performed a neuroimaging study including 3T MRI,...
Article
Introduction: Several structural and functional neuroimaging studies have shown that the Supplementary Motor Area (SMA) is affected by tau pathology in patients with Progressive Supranuclear Palsy (PSP). The aim of the study was to investigate the biochemical profile of SMA in PSP patients, using proton magnetic resonance spectroscopy (1H-MRS). M...
Poster
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Head motion is a most important confounding factors during fMRI data acquisition. One of its effect is misalignment of one volume to the next, introducing measurement inaccuracies as imaging voxels do not represent identical brain regions over time. An interesting approach to overcome this drawback could be represented by characterizing movements o...
Article
Psychogenic nonepileptic seizures (PNES) are episodes of paroxysmal impairment associated with a range of motor, sensory, and mental manifestations, which perfectly mimic epileptic seizures. Several patterns of neural abnormalities have been described without identifying a definite neurobiological substrate. In this multicenter cross-sectional stud...
Article
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Objective: It is well-known that the hippocampus presents significant asymmetry in Alzheimer's disease (AD) and that difference in volumes between left and right exists and varies with disease progression. However, few works investigated whether the asymmetry degree of subfields of hippocampus changes through the continuum from Mild Cognitive Impai...
Article
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Human genetic studies are rapidly identifying variants that increase risk for neurodevelopmental disorders. However, it remains unclear how specific mutations impact brain function and contribute to neuropsychiatric risk. Chromosome 16p11.2 deletion is one of the most common copy number variations in autism and related neurodevelopmental disorders....
Preprint
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Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives....
Conference Paper
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In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative...
Article
Alzheimer's Disease (AD) and Parkinson's Disease with Dementia (PDD), are characterized by a different mnesic failure, particularly in memory cued recall. Although hippocampal involvement has been shown in both these diseases, it remains unknown if a selective damage of specific subfields within the hippocampus may be responsible of the peculiar mn...
Article
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Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct su...
Article
Background: The application of artificial intelligence to extract predictors of Gambling disorder (GD) is a new field of study. A plethora of studies have suggested that maladaptive personality dispositions may serve as risk factors for GD. New method: Here, we used Classification and Regression Trees algorithm to identify multivariate predictiv...
Poster
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This work aimed at evaluating whether Machine Learning technique could support early diagnosis of Multiple Sclerosis (MS) from resting-state-functional (rs-fMRI) connectivity data. In particular, we explored the ability in distinguishing between controls and patients of mean signals extracted from ICA-components corresponding to 15 well-known netwo...
Poster
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Resting-state functional-MRI (rs-fMRI) is widely used to investigate the brain architecture networks though the BOLD response. The technique represents an interesting and reliable approach, but its elaboration results to be prone to noise due to confounding factors. In particular, head motion has become a particularly challenging problem in recent...
Conference Paper
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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA componen...
Article
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Objective Chefs exert expert motor and cognitive performances on a daily basis. Neuroimaging has clearly shown that that long-term skill learning (i.e., athletes, musicians, chess player or sommeliers) induces plastic changes in the brain thus enabling tasks to be performed faster and more accurately. How a chef's expertise is embodied in a specifi...
Article
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Introduction The presence of cognitive dysfunctions in Multiple Sclerosis (MS) has been well described as one of the most common co-morbidities [1-3], with a prevalence ranging from 45% to 65% [4]. The most affected cognitive domains in MS are memory, visuospatial perception, executive functions, attention and information processing speed [5]. Alth...
Article
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Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which r...
Article
This work evaluates the potential in diagnostic application of a new advanced neuroimaging method, which delineates the profile of tissue properties along the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS), by means of diffusion tensor imaging (DTI). Twenty-four ALS patients and 24 demographically matched healthy subjects were enr...
Chapter
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In questo nuovo testo è stata scelta la forma che interpreta l’attuale pensiero degli autori: la neuroradiologia una e trina (neuroradiologia diagnostica morfologica e funzionale, interventistica e pediatrica): non è possibile, infatti, di fronte a un quesito clinico, riservare a una sola metodica la soluzione; solo l’integrazione delle tecniche di...
Article
Several studies have demonstrated that religiosity is associated with specific personality traits, such as high Agreeableness/Conscientiousness or low Psychoticism. However, this evidence emerged by investigating active churchgoers with high religious practice or clerical individuals using the Eysenck’s taxonomy. This study explores, for the first...
Research
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In recent years, a high number of studies have demonstrated that neuropsychological functions are altered in multiple sclerosis (MS) patients with cerebellar lesions, mainly including attention, working memory and verbal fluency. Since the present literature is often elusive on this topic, we aim to provide a comprehensive report about the real imp...
Article
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In the last decade, both endocrine and ultrasound data have been tested to verify their usefulness for assessing ovarian reserve, but the ideal marker does not yet exist. The purpose of this study was to find, if any, a statistical advanced model able to identify a simple, easy to understand and intuitive modality for defining ovarian age by combin...
Conference Paper
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Recentstudieshaveshownthatfeaturesextractedfrombrain MRIs can successfully discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study describes a method that sequentially applies advanced feature selection techniques for finding the best subset of features in terms of binary classification accuracy. The classifiers that provide the...
Conference Paper
Full-text available
Background / Purpose: K-Surfer is a novel KNIME plug-in that contributes a number of nodes and meta nodes to integrate FreeSurfer and FSL data into KNIME. K-Surfer simplifies the importing of multi-dimensional data for group analysis based on the volume, thickness and diffusion data of neuroimages. Its user-friendly nodes configuration dialogues...
Conference Paper
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K-Surfer is a novel and unique KNIME plug-in for brain MRI data, which facilitates the design and deployment of fully automated workflows for extracting, managing and mining FreeSurfer and FSL data.
Article
A questionnaire is a method for collecting data that can come from many sources such as observations, telephone interviews or documentary sources. Whatever the source of data is, the questionnaire provides a framework of questions that facilitate researcher’s work. A manual approach for collecting data using questionnaire presents some limitations...
Conference Paper
The increasing number of people affected by Neurodegenerative diseases and the improvement of brain imaging diagnostic techniques are bringing to a massive production of brain images that need demanding preprocessing and analysis algorithms. We analyzed volumetric measures of critical brain areas by using different Data Mining methods. Structural m...
Article
Data mining (DM) is increasingly used in the analysis of data generated in life sciences, including biological data produced in several disciplines such as genomics and proteomics, medical data produced in clinical practice, and administrative data produced in health care. The difficulty in mining such data is twofold. First of all, data in life sc...