A Prehospital Triage System to Detect Traumatic Intracranial Hemorrhage Using Machine Learning Algorithms
Sign Up to like & getrecommendations! Published in 2022 at "JAMA Network Open"
DOI: 10.1001/jamanetworkopen.2022.16393
Abstract: Key Points Question Can machine learning algorithms be used to triage patients with head trauma according to their severity before transportation? Findings In this cohort study of 2123 patients with head trauma, a machine learning–based… read more here.
Keywords: learning algorithms; triage; machine; traumatic intracranial ... See more keywords
Identification of essential tremor based on resting‐state functional connectivity
Sign Up to like & getrecommendations! Published in 2022 at "Human Brain Mapping"
DOI: 10.1002/hbm.26124
Abstract: Currently, machine‐learning algorithms have been considered the most promising approach to reach a clinical diagnosis at the individual level. This study aimed to investigate whether the whole‐brain resting‐state functional connectivity (RSFC) metrics combined with machine‐learning… read more here.
Keywords: learning algorithms; machine; machine learning; resting state ... See more keywords
Machine learning algorithms for predicting direct‐acting antiviral treatment failure in chronic hepatitis C: An HCV‐TARGET analysis
Sign Up to like & getrecommendations! Published in 2022 at "Hepatology"
DOI: 10.1002/hep.32347
Abstract: We aimed to develop and validate machine learning algorithms to predict direct‐acting antiviral (DAA) treatment failure among patients with HCV infection. read more here.
Keywords: learning algorithms; machine learning; treatment failure; direct acting ... See more keywords
Machine learning algorithms for smart and intelligent healthcare system in Society 5.0
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23061
Abstract: The pandemic has shown us that it is quite important to keep track record our health digitally. And at the same time, it also showed us the great potential of Instruments like wearable observing gadgets,… read more here.
Keywords: information; intelligent; learning algorithms; machine learning ... See more keywords
Hyperspectral Plant Sensing for Differentiating Glyphosate-Resistant and Glyphosate-Susceptible Johnsongrass through Machine Learning Algorithms.
Sign Up to like & getrecommendations! Published in 2022 at "Pest management science"
DOI: 10.1002/ps.6864
Abstract: Johnsongrass (Sorghum halepense) is one of the weeds that evolves resistance to glyphosate [N-(phosphonomethyl)-glycine], the most widely used herbicide, and the weed may cause agronomic troublesome in the southern United States. This paper reports a… read more here.
Keywords: glyphosate; learning algorithms; machine; machine learning ... See more keywords
Machine learning algorithms predict within one size of the final implant ultimately used in total knee arthroplasty with good-to-excellent accuracy
Sign Up to like & getrecommendations! Published in 2022 at "Knee Surgery, Sports Traumatology, Arthroscopy"
DOI: 10.1007/s00167-022-06866-y
Abstract: To develop a novel machine learning algorithm capable of predicting TKA implant sizes using a large, multicenter database. A consecutive series of primary TKA patients from two independent large academic and three community medical centers… read more here.
Keywords: size; machine; learning algorithms; machine learning ... See more keywords
Artificial intelligence for MRI diagnosis of joints: a scoping review of the current state-of-the-art of deep learning-based approaches
Sign Up to like & getrecommendations! Published in 2021 at "Skeletal Radiology"
DOI: 10.1007/s00256-021-03830-8
Abstract: Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A variety of investigational deep learning algorithms have been developed to detect… read more here.
Keywords: learning; deep learning; learning algorithms; radiology ... See more keywords
Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features
Sign Up to like & getrecommendations! Published in 2020 at "European Radiology"
DOI: 10.1007/s00330-020-07064-5
Abstract: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Retrospectively, 73 patients… read more here.
Keywords: machine learning; assessment categories; analysis; prostate cancer ... See more keywords
Impact of multilayer ELM feature mapping technique on supervised and semi-supervised learning algorithms
Sign Up to like & getrecommendations! Published in 2022 at "Soft Computing"
DOI: 10.1007/s00500-021-06387-9
Abstract: The popularity of deep learning architecture is increasing day by day. But the majority of deep learning algorithms have their own limitations, such as slow convergence, high training time, sensitivity to noisy data, the problem… read more here.
Keywords: multilayer elm; learning algorithms; multilayer; feature mapping ... See more keywords
Deep learning for fake news detection on Twitter regarding the 2019 Hong Kong protests
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-06230-0
Abstract: The dissemination of fake news on social media platforms is an issue of considerable interest, as it can be used to misinform people or lead them astray, which is particularly concerning when it comes to… read more here.
Keywords: news; hong kong; deep learning; learning algorithms ... See more keywords
Electrodiagnostic accuracy in polyneuropathies: supervised learning algorithms as a tool for practitioners
Sign Up to like & getrecommendations! Published in 2020 at "Neurological Sciences"
DOI: 10.1007/s10072-020-04499-y
Abstract: Objective The interpretation of electrophysiological findings may lead to misdiagnosis in polyneuropathies. We investigated the electrodiagnostic accuracy of three supervised learning algorithms (SLAs): shrinkage discriminant analysis, multinomial logistic regression, and support vector machine (SVM), and… read more here.
Keywords: accuracy polyneuropathies; accuracy; learning algorithms; polyneuropathies supervised ... See more keywords