Search results for "machine"
showing 10 items of 2592 documents
MRI radiomics-based machine-learning classification of bone chondrosarcoma.
2019
Abstract Purpose To evaluate the diagnostic performance of machine learning for discrimination between low-grade and high-grade cartilaginous bone tumors based on radiomic parameters extracted from unenhanced magnetic resonance imaging (MRI). Methods We retrospectively enrolled 58 patients with histologically-proven low-grade/atypical cartilaginous tumor of the appendicular skeleton (n = 26) or higher-grade chondrosarcoma (n = 32, including 16 appendicular and 16 axial lesions). They were randomly divided into training (n = 42) and test (n = 16) groups for model tuning and testing, respectively. All tumors were manually segmented on T1-weighted and T2-weighted images by drawing bidimensiona…
''Modulation of Anticipatory Postural Activity For Multiple Conditions of A Whole-body Pointing Task''
2012
Tolambiya, A. | Chiovetto, E. | Pozzo, T. | Thomas, E.; International audience; ''This is a study on associated postural activities during the anticipatory segments of a multijoint movement. Several previous studies have shown that they are task dependant. The previous studies, however, have mostly been limited in demonstrating the presence of modulation for one task condition, that is, one aspect such as the distance of the target or the direction of reaching. Real-life activities like whole-body pointing, however, can vary in several ways. How specific is the adaptation of the postural activities for the diverse possibilities of a whole-body pointing task? We used a classification paradig…
Local staging of rectal carcinoma and assessment of the circumferential resection margin with high-resolution MRI using an integrated parallel acquis…
2005
Purpose To assess the diagnostic accuracy of integrated parallel acquisition technique (iPAT) in local staging of rectal carcinoma in comparison to conventional high-resolution MRI. Materials and Methods A total of 28 patients with a neoplasm of the rectum and 15 control patients underwent MRI of the pelvis. High-resolution images were acquired conventionally and with iPAT using a modified sensitivity encoding (mSENSE). Image quality, signal-to-noise and contrast-to-noise ratios (SNR, CNR), tumor extent, nodal status, and delineation of the circumferential resection margin (CRM) were compared. In 19 patients with a carcinoma, MR findings were correlated with the histopathological diagnosis.…
Focal breast lesion characterization according to the BI-RADS US lexicon: role of a computer-aided decision-making support
2018
Objectives: to assess the diagnostic performance of a computer-guided decision- making software (S-Detect) in the US characterization of focal breast lesions (FBLs), according to the radiologist's experience. Materials and Methods: 300 FBLs (size: 2.6-47.2 mm; mean: 13.2 mm) in 255 patients (mean age: 51 years) were prospectively assessed in consensus according to BIRADS US lexicon by two experienced radiologists without and with S-Detect; to evaluate intra and inter-observer agreement, the same 300 FBLs were independently evaluated by two residents at baseline and after 3 months. Results: 120/300 (40%) FBLs were malignant, 2/300 (0.7%) high-risk and 178/300 (59.3%) benign. Experts review s…
Daily changes of individual gait patterns identified by means of support vector machines.
2016
Despite the common knowledge about the individual character of human gait patterns and about their non-repeatability, little is known about their stability, their interactions and their changes over time. Variations of gait patterns are typically described as random deviations around a stable mean curve derived from groups, which appear due to noise or experimental insufficiencies. The purpose of this study is to examine the nature of intrinsic inter-session variability in more detail by proving separable characteristics of gait patterns between individuals as well as within individuals in repeated measurement sessions. Eight healthy subjects performed 15 gait trials at a self-selected spee…
Decoding Musical Training from Dynamic Processing of Musical Features in the Brain
2018
AbstractPattern recognition on neural activations from naturalistic music listening has been successful at predicting neural responses of listeners from musical features, and vice versa. Inter-subject differences in the decoding accuracies have arisen partly from musical training that has widely recognized structural and functional effects on the brain. We propose and evaluate a decoding approach aimed at predicting the musicianship class of an individual listener from dynamic neural processing of musical features. Whole brain functional magnetic resonance imaging (fMRI) data was acquired from musicians and nonmusicians during listening of three musical pieces from different genres. Six mus…
Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry
2019
[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (S…
On the complementarity of holistic and analytic approaches to performance assessment scoring.
2019
BACKGROUND A holistic approach to performance assessment recognizes the theoretical complexity of multifaceted critical thinking (CT), a key objective of higher education. However, issues related to reliability, interpretation, and use arise with this approach. AIMS AND METHOD Therefore, we take an analytic approach to scoring students' written responses on a performance assessment. We focus on the complementarity of holistic and analytic approaches and on whether theoretically developed analytical scoring rubrics can produce sub-scores that may measure the 'whole' performance in a holistic assessment. SAMPLE We use data from the Wind Turbines performance assessment, developed in the iPAL p…
Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: A preliminary study.
2022
Purpose A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with Hodgkin Lymphoma (HL). Materials and methods Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra T…
Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes
2015
[EN] Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and patient classification is done afterwards, when its clinical course is available. In this paper we present a comparison of classification performances when differentiating paroxysmal and persistent atrial fibrillation episodes by means of support vector machines. We analyze short surface electrocardiogram recordings by extracting modulus and phase features from several time-frequency transforms: short-time Fourier transform, Wigner-Ville, Choi-…