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The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging.

BMC medical imaging
BACKGROUND: White matter hyperintensities (WMHs) are closely associated with cognitive frailty (CF). This study aims to explore the potential diagnostic value of WMHs for CF based on radiomics approaches, thereby providing a novel methodology for the...

Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau.

Scientific reports
No predictive models have been reported for tracheostomy extubation success in plateau region rehabilitation departments. Hence, the primary objective of this retrospective study was to evaluate the predictive capabilities of different models for ext...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Scientific reports
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...

Metabolic profiles in laryngeal cancer defined two distinct molecular subtypes with divergent prognoses.

Frontiers in immunology
BACKGROUND: Laryngeal cancer (LCA) is the second most common type of head and neck malignancy, characterized by high recurrence rates and poor overall survival (OS). However, progress in curing LCA through molecular-targeted diagnostics and therapies...

Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surveillance documentation patterns to predict deterioration risks for hospitalized patients. In a retros...

Performance of multimodal prediction models for intracerebral hemorrhage outcomes using real-world data.

International journal of medical informatics
BACKGROUND: We aimed to develop and validate multimodal models integrating computed tomography (CT) images, text and tabular clinical data to predict poor functional outcomes and in-hospital mortality in patients with intracerebral hemorrhage (ICH). ...

Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.

Cardiovascular diabetology
BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six ...

Development of a risk prediction model for secondary infection in severe/critical COVID-19 patients.

BMC infectious diseases
OBJECTIVE: This study aimed to develop a predictive model for secondary infections in patients with severe or critical COVID-19 by analyzing clinical characteristics and laboratory indicators.

Synthesizing [F]PSMA-1007 PET bone images from CT images with GAN for early detection of prostate cancer bone metastases: a pilot validation study.

BMC cancer
BACKGROUND: [F]FDG PET/CT scan combined with [F]PSMA-1007 PET/CT scan is commonly conducted for detecting bone metastases in prostate cancer (PCa). However, it is expensive and may expose patients to more radiation hazards. This study explores deep l...

Metabolic signature of COVID-19 progression: potential prognostic markers for severity and outcome.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: There are significant challenges remain in accurately categorizing the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients.