Results 51 to 60 of about 8,989,075 (297)

Classifying Dysphagic Swallowing Sounds with Support Vector Machines [PDF]

Healthcare, 2020
Swallowing sounds from cervical auscultation include information related to the swallowing function. Several studies have been conducted on the screening tests of dysphagia. The literature shows a significant difference between the characteristics of swallowing sounds obtained from different subjects (e.g., healthy and dysphagic subjects; young and old
Shigeyuki Miyagi, Syo Sugiyama, Keiko Kozawa, Sueyoshi Moritani, Shin-ichi Sakamoto, Osamu Sakai   +5 more
openaire   +2 more sources

Support Vector Machines for Credit Scoring and discovery of significant features [PDF]

, 2009
The assessment of risk of default on credit is important for financial institutions. Logistic regression and discriminant analysis are techniques traditionally used in credit scoring for determining likelihood to default based on consumer application and
Crook, Jonathan, Bellotti, Tony
core   +1 more source

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

Prediction of generalized anxiety levels during the Covid-19 pandemic: A machine learning-based modeling approach

Informatics in Medicine Unlocked, 2022
The rapid spread of the Covid-19 outbreak led many countries to enforce precautionary measures such as complete lockdowns. These lifestyle-altering measures caused a significant increase in anxiety levels globally. For that reason, decision-makers are in
Faisal Mashel Albagmi, Aisha Alansari, Deema Saad Al Shawan, Heba Yaagoub AlNujaidi, Sunday O. Olatunji   +4 more
doaj   +1 more source

Massive Data Classification via Unconstrained Support Vector Machines [PDF]

, 2006
A highly accurate algorithm, based on support vector machines formulated as linear programs [13, 1], is proposed here as a completely unconstrained minimization problem [15].
O. L. Mangasarian, Mangasarian, Olvi, Thompson, Michael, M. E. Thompson   +3 more
core   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data [PDF]

, 2013
Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for ...
Thomas Kirste, Stefan J. Teipel (417223), Stefan J. Teipel, Fellgiebel, Andreas, Karlheinz Hauenstein (417221), Hauenstein, K., Kilimann, I., Harald Hampel, Thomas Kirste (417222), Dyrba, M., Kirste, Thomas, Bokde, A.L.W., Kilimann, Ingo, Annahita Oswald, Pievani, M., Filippi, M., Martin Dyrba (417214), Ewers, Michael, Martin Wegrzyn, Hauenstein, Karlheinz, Ewers, M., Klöppel, Stefan, Arun L. W. Bokde (206207), Pievani, Michela, Oswald, Annahita, Michela Pievani, EDSD, [Study group], Claudia Plant, Klöppel, S., Karlheinz Hauenstein, Andreas Fellgiebel, Michael Ewers (317132), Massimo Filippi, Thomas Meindl, Arun L W Bokde, Martin Dyrba, Plant, C., Wegrzyn, Martin, Teipel, Stefan, Thomas Meindl (417219), Massimo Filippi (110054), Filippi, Massimo, Claudia Plant (417217), Bokde, Arun L. W., Wegrzyn, M., Kirste, T., Hampel, Harald, Andreas Fellgiebel (382233), Stefan Klöppel (261558), Annahita Oswald (417218), Arun L. W. Bokde, EDSD study group, Meindl, Thomas, Michael Ewers, Ingo Kilimann, EDSD Study Group (), Martin Wegrzyn (417215), Stefan Klöppel, Stefan J Teipel, Michela Pievani (417220), Hampel, H., Plant, Claudia, Harald Hampel (183230), Oswald, A., Teipel, Stefan J., Meindl, T., Teipel, S.J., Ingo Kilimann (417216), Fellgiebel, A., Dyrba, Martin   +69 more
core   +2 more sources

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Leveraging Machine Learning for Fraudulent Social Media Profile Detection

Cybernetics and Information Technologies
Fake social media profiles are responsible for various cyber-attacks, spreading fake news, identity theft, business and payment fraud, abuse, and more. This paper aims to explore the potential of Machine Learning in detecting fake social media profiles ...
Ramdas Soorya, Agnes Neenu N. T.
doaj   +1 more source

An exploration of machine learning approaches for early Autism Spectrum Disorder detection

Healthcare Analytics
Autism Spectrum Disorder is a neurodevelopmental condition impacting an individual’s repetitive behaviours, social skills, verbal and nonverbal communication abilities, and capacity for acquiring new knowledge.
Nawshin Haque, Tania Islam, Md Erfan
doaj   +1 more source