Results 181 to 190 of about 40,856 (264)

Quantitative assessment of gait alterations and variability in sulky‐driven Standardbred trotters after a standardised exercise test

Equine Veterinary Journal, EarlyView.
Abstract Background Assessment of equine metabolic and locomotory responses to quantified levels of physical exercise is needed to support the creation of tailored protocols for optimal training adaptation. The locomotory response to exercise in horses is not fully understood.
Rhana Mackie Aarts, Ineke Hillie Smit, Guilherme de Camargo Ferraz, Marie Rhodin, Filipe Manuel Serra Braganca, Elin Hernlund   +5 more
wiley   +1 more source

Enhancing Hypertension Risk Diagnosis Using a Hybrid Machine Learning Framework: Leveraging Body Composition Data. [PDF]

Biomed Res Int
Mirzaye AW, Saadatfar H, Nematollahi MA, Banerjee B.   +3 more
europepmc   +1 more source

The effect of full‐limb flexion tests on static and dynamic muscle activity and locomotion asymmetry in owner‐sound horses

Equine Veterinary Journal, EarlyView.
Abstract Background Flexion tests are commonly used in equine locomotion examinations to identify underlying locomotor issues, yet their neuromuscular effects remain poorly understood. Response variability raises concerns about their clinical value in lameness assessments and pre‐purchase evaluations.
Marijke Jonkhart, Filipe M. Serra Bragança, Ineke H. Smit, Harold Brommer, Jozef J. M. Suskens   +4 more
wiley   +1 more source

Robust evaluation of classical and quantum machine learning under noise, imbalance, feature reduction and explainability. [PDF]

Sci Rep
Sheoran SK, Yadav V, Sheoran RK.
europepmc   +1 more source

Exploring and Explaining the Use and Proliferation of Whole Life Orders in England and Wales

The Howard Journal of Crime and Justice, EarlyView.
ABSTRACT Whole life orders (WLOs) represent the power of the state to inflict harm at its most extreme, with such sentences being found to be in breach of the European Convention on Human Rights. However, very little research has endeavoured to understand the use of WLOs.
Hannah Gilman, Jake Phillips
wiley   +1 more source

A machine learning approach for opioid overdose risk prediction among Alabama Medicaid beneficiaries with opioid prescriptions. [PDF]

Sci Rep
Parton J, Wang Q, Wang EC, Hanson C, Higginbotham JA.   +4 more
europepmc   +1 more source

Machine Learning Model for Predicting Postoperative Pain in Cases of Irreversible Pulpitis

International Endodontic Journal, EarlyView.
ABSTRACT Aim Postoperative pain is a frequent clinical concern following endodontic treatment. This study aimed to develop and validate supervised machine learning models to predict the occurrence of postoperative pain in cases of irreversible pulpitis.
Pedro Felipe de Jesus Freitas, Ingrid Luiza Mendonça Cunha, Thalita de Paris Matos, Flares Baratto‐Filho, Bianca Marques de Mattos de Araujo, Manoel Damião Sousa‐Neto, Leandro de Moura Martins, Fernando José Herkrath, Emílio Carlos Sponchiado‐Júnior, Cristiano Miranda de Araujo   +9 more
wiley   +1 more source

Cardiovascular risk prediction via ensemble machine learning and oversampling methods. [PDF]

Sci Rep
Reátegui R, Tandazo-Malla C, Suárez R, Ramírez-Cerna L.   +3 more
europepmc   +1 more source

Nurse Leadership and Artificial Intelligence Integration in Nursing Workforce Management: A Scoping Review

Journal of Advanced Nursing, EarlyView.
ABSTRACT Aim To systematically map evidence on the application of AI systems in nursing workforce management, with a targeted focus on the role of nurse leaders. Design A scoping review. Data Sources A comprehensive literature search was conducted across six databases: CINAHL, IEEE Xplore, MEDLINE/PubMed, PsycINFO, Scopus, and Web of Science.
Frank Kiwanuka, Simone Stevanin, Younas Ahtisham, Brenda Owusu, Anu Nurmeksela, Tarja Kvist   +5 more
wiley   +1 more source

High accuracy breast cancer classification with BIRADS and coclustering. [PDF]

PLoS One
Zhou R, Yu X, Wang J.
europepmc   +1 more source