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
Assisting the Diagnosis of Cirrhosis in Chronic Hepatitis C Patients Based on Machine Learning Algorithms: A Novel Non‐Invasive Approach
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Clinical Laboratory Analysis"
DOI: 10.1002/jcla.70054
Abstract: This study aimed to determine the important features and cut‐off values after demonstrating the detectability of cirrhosis using routine laboratory test results of chronic hepatitis C (CHC) patients in machine learning (ML) algorithms. read more here.
Keywords: learning algorithms; chronic hepatitis; cirrhosis; 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
Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms
Sign Up to like & getrecommendations! Published in 2025 at "Veterinary Medicine and Science"
DOI: 10.1002/vms3.70420
Abstract: ABSTRACT Background Machine learning systems learn from historical data to forecast future outcomes. In the context of livestock farming, machine learning can be utilized to predict variables such as growth rates, milk production and breeding… read more here.
Keywords: weaning weight; machine; machine learning; predicting weaning ... 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
A general framework of high-performance machine learning algorithms: application in structural mechanics
Sign Up to like & getrecommendations! Published in 2024 at "Computational Mechanics"
DOI: 10.1007/s00466-023-02386-9
Abstract: Data-driven models utilizing powerful artificial intelligence (AI) algorithms have been implemented over the past two decades in different fields of simulation-based engineering science. Most numerical procedures involve processing data sets developed from physical or numerical… read more here.
Keywords: machine learning; mechanics; performance; learning algorithms ... See more keywords