OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression in patients with major depressive disorder (MDD) and bipolar disorder (BD), but accurate prediction of treatment response remains a challenge. Th...
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Nov 1, 2025
OBJECTIVE: To develop and validate advanced machine learning (ML) models for predicting unplanned intrapartum cesarean deliveries in women with no previous cesarean delivery, using both static and dynamic clinical data.
Wastewater greenhouse gas (GHG) emissions represent a complex system characterized by distinct spatial-temporal patterns influenced by various drivers. This study examined the spatiotemporal heterogeneity of wastewater GHG emission intensity and tota...
IEEE transactions on bio-medical engineering
Oct 1, 2025
Sleep spindles, which are key biomarkers of non-rapid eye movement stage 2 sleep, play a crucial role in predicting outcomes for patients with acute disorders of consciousness (ADOC). However, several critical challenges remain in spindle detection: ...
INTRODUCTION: Individuals with spinal cord injury (SCI) have varying bladder health trajectories after their injury. We explored whether a predictive machine learning model could identify which variables impact urinary symptoms.
Idiopathic multicentric Castleman disease (iMCD) is a rare lymphoproliferative disorder classified into three recognized clinical subtypes-idiopathic plasmacytic lymphadenopathy (IPL), TAFRO, and NOS. Although clinical criteria are available for subt...
Atypia of Undetermined Significance (AUS), classified as Category III in the Bethesda Thyroid Cytopathology Reporting System, presents significant diagnostic challenges for clinicians. This study aims to develop a clinical decision support system tha...
This paper tested the relevance of two machine learning approaches (decision trees, DTs; and random forest models, RFs) applied to meat authentication. DT allow to select and rank potential biomarkers according to their respective discriminatory powe...
BACKGROUND: The Aberrant Salience (AS) model conceptualizes psychosis onset as the altered attribution of salience to neutral stimuli. The Aberrant Salience Inventory (ASI), a psychometric tool, measures this phenomenon. This study utilized a multi-c...
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