IATSS ResearchMotorcycle crashes represent a major road safety challenge, particularly in developing countries. This study analyzes motorcycle crash injury severity on intercity roads in Iran using an integrated framework combining classical statistical models and ...
Amirhassan Kermanshah +2 more
doaj +1 more source
Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
wiley +1 more source
Towards an explainable machine learning model to reduce readmission risks for diabetes patients
Informatics in Medicine UnlockedObjective:: Hospital readmission of Diabetes patients is a persistent burden on the healthcare industry. Artificial Intelligence (AI) based Machine Learning (ML) techniques offer the potential to predict readmission rates and related risk features for ...
Changfeng Guo +5 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
On Leveraging Machine Learning in Sport Science in the Hypothetico-deductive Framework
Sports Medicine - OpenSupervised machine learning (ML) offers an exciting suite of algorithms that could benefit research in sport science. In principle, supervised ML approaches were designed for pure prediction, as opposed to explanation, leading to a rise in powerful, but ...
Jordan Rodu +3 more
doaj +1 more source
Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model [PDF]
PeerJBackground Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing ...
Bihua Yao +7 more
doaj +2 more sources
Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source
Interpretable Multiclass Models for Corporate Credit Rating Capable of Expressing Doubt
Frontiers in Applied Mathematics and Statistics, 2016 Corporate credit rating is a process to classify commercial enterprises based on their creditworthiness. Machine learning algorithms can construct classification models, but in general they do not tend to be 100% accurate.
Lennart Obermann, Stephan Waack
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Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Monitoring the Centennial Variation of Heavy Metals in Lake Sediments and Influencing Factors Using Environmental Magnetism and Machine Learning Methods [PDF]
E3S Web of ConferencesThe association between the magnetic properties of lake sediments and heavy metal(loid)s (HMs) is well-documented; however, their correlation with the chemical fractions of HMs remains under-investigated.
Deng Ligang, Li Huiming, Qian Xin
doaj +1 more source