Search results for "Machine"
showing 10 items of 2592 documents
The VEPSY UPDATED Project: Clinical Rationale and Technical Approach.
2003
More than 10 years ago, Tart (1990) described virtual reality (VR) as a technological model of consciousness offering intriguing possibilities for developing diagnostic, inductive, psychotherapeutic, and training techniques that can extend and supplement current ones. To exploit and understand this potential is the overall goal of the "Telemedicine and Portable Virtual Environment in Clinical Psychology"--VEPSY UPDATED--a European Community-funded research project (IST-2000-25323, www.cybertherapy.info). Particularly, its specific goal is the development of different PC-based virtual reality modules to be used in clinical assessment and treatment of social phobia, panic disorders, male sexu…
Estimating Exposome Score for Schizophrenia Using Predictive Modeling Approach in Two Independent Samples: The Results From the EUGEI Study
2019
The EUGEI project was supported by the grant agreement HEALTH-F2-2010-241909 from the European Community’s Seventh Framework Programme. The authors are grateful to the patients and their families for participating in the project. They also thank all research personnel involved in the GROUP project, in particular J. van Baaren, E. Veermans, G. Driessen, T. Driesen, E. van’t Hag and J. de Nijs. Bart PF Rutten was funded by a VIDI award number 91718336 from the Netherlands Scientific Organisation.
Hypothermic Oscillating Liver Perfusion Stimulates ATP Synthesis prior to Transplantation
1998
Abstract Background. ATP and glycogen depletion often have been demonstrated during cold storage of the liver prior to transplantation. Suppression of events that lead to metabolic depression and to lipid peroxidation could contribute to improvement of liver preservation. A new method of liver preservation for transplantation is therefore suggested, an oscillating oxygenated hypothermic liver perfusion. Methods. Biochemical analysis of liver tissue samples and perfusate after 10 h of perfusion by the presented oscillating perfusion model were compared with results after continuous liver perfusion for 10 h as well as with data derived from cold-stored livers over a period of 10 h. Particular…
A new machine learning approach for predicting the response to anemia treatment in a large cohort of End Stage Renal Disease patients undergoing dial…
2015
Chronic Kidney Disease (CKD) anemia is one of the main common comorbidities in patients undergoing End Stage Renal Disease (ESRD). Iron supplement and especially Erythropoiesis Stimulating Agents (ESA) have become the treatment of choice for that anemia. However, it is very complicated to find an adequate treatment for every patient in each particular situation since dosage guidelines are based on average behaviors, and thus, they do not take into account the particular response to those drugs by different patients, although that response may vary enormously from one patient to another and even for the same patient in different stages of the anemia. This work proposes an advance with respec…
Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricu…
2019
Background: Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms. Methods: Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute–right ventricular fail…
Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning …
2021
Objective: The aim of this study was (1) to investigate the application of texture analysis of choline PET/CT images in prostate cancer (PCa) patients and (2) to propose a machine-learning radiomics model able to select PET features predictive of disease progression in PCa patients with a same high-risk class at restaging. Material and methods: Ninety-four high-risk PCa patients who underwent restaging Cho-PET/CT were analyzed. Follow-up data were recorded for a minimum of 13 months after the PET/CT scan. PET images were imported in LIFEx toolbox to extract 51 features from each lesion. A statistical system based on correlation matrix and point-biserial-correlation coefficient has been impl…
Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging
2017
International audience; Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed improving diagnosis. In practice, diagnosis is affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and diagnosis (CAD) systems are being designed to help radiologists in their clinical practice. We propose a CAD system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, diffusion weighted (DW)-MRI, MRSI). The aim of this CAD system was to provide a probabilistic map of cancer…
Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic…
2017
[EN] The purpose of this study was to differentiate acute from chronic myocardial infarction using machine learning techniques and texture features extracted from cardiac magnetic resonance imaging (MRI). The study group comprised 22 cases with acute myocardial infarction (AMI) and 22 cases with chronic myocardial infarction (CMI). Cine and late gadolinium enhancement (LGE) MRI were analyzed independently to differentiate AMI from CMI. A total of 279 texture features were extracted from predefined regions of interest (ROIs): the infarcted area on LGE MRI, and the entire myocardium on cine MRI. Classification performance was evaluated by a nested cross-validation approach combining a feature…
Choline PET/CT Features to Predict Survival Outcome in High Risk Prostate Cancer Restaging: A Preliminary Machine-Learning Radiomics Study
2020
Background Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging but to date its role has not been investigated for Cho-PET in prostate cancer. The potential application of radiomics features analysis using a machine-learning radiomics algorithm was evaluated to select 18F-Cho PET/CT imaging features to predict disease progression in PCa. Methods We retrospectively analyzed high-risk PCa patients who underwent restaging 18F-Cho PET/CT from November 2013 to May 2018. 18F-Cho PET/CT studies and related structures containing volumetric segmentations were imported in the "CGITA" toolbox to extract imaging features from each lesion. A Machine-learning model h…
Prognostic Impact of Frozen Section Investigation and Extent of Proximal Safety Margin in Gastric Cancer Resection
2020
Background and aims Guidelines propose different extents of macroscopic proximal margin for gastric cancer and frozen margin investigation in selected cases, but data is lacking. This study was to evaluate the necessary extent of macroscopic proximal margin, accuracy of frozen margin investigation, and prognostic impact of tumor-free proximal margin length in pT2-pT4 gastric cancer. Study design Proximal and distal frozen margins were routinely investigated intraoperatively in all pT2-pT4 gastric cancers resected between 2011 and 2017. Macroscopic and microscopic proximal margin lengths were correlated. For R0-resections, survival analysis was performed for distal gastrectomy (DG) with micr…