AIMC Topic: Middle Aged
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Specific Contribution of the Cerebellar Inferior Posterior Lobe to Motor Learning in Degenerative Cerebellar Ataxia.
Cerebellum (London, England)
Jul 16, 2025
BACKGROUND AND OBJECTIVE: Degenerative cerebellar ataxia, a group of progressive neurodegenerative disorders, is characterised by cerebellar atrophy and impaired motor learning. Using CerebNet, a deep learning algorithm for cerebellar segmentation, t...
Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.
PloS one
Jul 16, 2025
BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often...
Plasma Metabolomics and Machine Learning Reveals Metabolic Alterations and Diagnostic Biomarkers for Deep Venous Thrombosis in Hypertensive Patients after Traumatic Fracture.
Journal of proteome research
Jul 15, 2025
We aimed to explore the metabolic dysregulations and diagnostic biomarkers for post-traumatic deep venous thrombosis (pt-DVT) in hypertensive (HPT) patients after fracture. An untargeted ultraperformance liquid chromatography-mass spectrometry-based ...
Assessing inflammatory protein biomarkers in COPD subjects with and without alpha-1 antitrypsin deficiency.
Respiratory research
Jul 15, 2025
RATIONALE: Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT deficiency (AATD) suggests that inflammatory processes may contribute to COPD risk indepe...
Multi-transcriptomics predicts clinical outcome in systemically untreated breast cancer patients with extensive follow-up.
Breast cancer research : BCR
Jul 15, 2025
BACKGROUND: Prognostic tools for determining patients with indolent breast cancers (BCs) are far from optimal, leading to extensive overtreatment. Several studies have demonstrated mRNAs, lncRNAs and miRNAs to have prognostic potential in BC. Because...
An interpretable machine learning model for predicting bone marrow invasion in patients with lymphoma via F-FDG PET/CT: a multicenter study.
BMC medical informatics and decision making
Jul 15, 2025
PURPOSE: Accurate identification of bone marrow invasion (BMI) is critical for determining the prognosis of and treatment strategies for lymphoma. Although bone marrow biopsy (BMB) is the current gold standard, its invasive nature and sampling errors...
Development and external validation of a machine learning model for predicting drug-induced immune thrombocytopenia in a real-world hospital cohort.
BMC medical informatics and decision making
Jul 15, 2025
BACKGROUND: Drug-induced immune thrombocytopenia (DITP) is a rare but potentially life-threatening adverse drug reaction, often underrecognized due to its nonspecific presentation and the lack of real-time diagnostic tools. Early identification of at...
Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.
BMC medical informatics and decision making
Jul 15, 2025
BACKGROUND: Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), characterized by high incidence, elevated mortality rates, and substantial therapeutic challenges. Accurate prediction of mortality in patients with hemorr...
Non-invasive liver fibrosis screening on CT images using radiomics.
BMC medical imaging
Jul 15, 2025
PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of the liver.
Ultrafast T2-weighted MR imaging of the urinary bladder using deep learning-accelerated HASTE at 3 Tesla.
BMC medical imaging
Jul 15, 2025
OBJECTIVE: This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifac...
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