AIMC Topic: Retrospective Studies

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Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Cardiovascular diabetology Jan 8, 2025
Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessing stress hyperglycemia, which has been correlated with adverse outcomes in various major diseases. H...
Biomarkers Prognosis Retrospective Studies Intensive Care Units Female Risk Factors Aged Aged, 80 and over Male Humans Machine Learning Decision Support Techniques Databases, Factual Hyperglycemia Chronic Disease Middle Aged Predictive Value of Tests Risk Assessment Patient Admission Cause of Death Blood Glucose Heart Failure Time Factors
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Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction.

AJNR. American journal of neuroradiology Jan 8, 2025
BACKGROUND AND PURPOSE: DWI is crucial for detecting infarction stroke. However, its spatial resolution is often limited, hindering accurate lesion visualization. Our aim was to evaluate the image quality and diagnostic confidence of deep learning (D...
Stroke Humans Retrospective Studies Image Interpretation, Computer-Assisted Female Signal-To-Noise Ratio Aged Diffusion Magnetic Resonance Imaging Aged, 80 and over Adult Male Middle Aged Deep Learning
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Multimodal data deep learning method for predicting symptomatic pneumonitis caused by lung cancer radiotherapy combined with immunotherapy.

Frontiers in immunology Jan 8, 2025
OBJECTIVES: The pairing of immunotherapy and radiotherapy in the treatment of locally advanced nonsmall cell lung cancer (NSCLC) has shown promise. By combining radiotherapy with immunotherapy, the synergistic effects of these modalities not only bol...
Lung Neoplasms Humans Immunotherapy Retrospective Studies Carcinoma, Non-Small-Cell Lung Aged Tomography, X-Ray Computed Radiation Pneumonitis Pneumonia Male Female Middle Aged Combined Modality Therapy Deep Learning
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Interpretable machine learning-based prediction of 28-day mortality in ICU patients with sepsis: a multicenter retrospective study.

Frontiers in cellular and infection microbiology Jan 8, 2025
BACKGROUND: Sepsis is a major cause of mortality in intensive care units (ICUs) and continues to pose a significant global health challenge, with sepsis-related deaths contributing substantially to the overall burden on healthcare systems worldwide. ...
Male Middle Aged Sepsis Support Vector Machine Logistic Models Retrospective Studies Humans Intensive Care Units Machine Learning Female Algorithms Risk Factors Prognosis Aged
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Longitudinal twin growth discordance patterns and adverse perinatal outcomes.

American journal of obstetrics and gynecology Jan 7, 2025
BACKGROUND: Growth discordance in twin pregnancies is associated with increased perinatal morbidity and mortality, yet the patterns of discordance progression and the utility of Doppler assessments remain underinvestigated.
Retrospective Studies Pregnancy Female Infant, Newborn Adult Humans Machine Learning Middle Cerebral Artery Fetal Growth Retardation Umbilical Arteries Perinatal Mortality Pregnancy, Twin Ultrasonography, Prenatal Pregnancy Outcome Longitudinal Studies Ultrasonography, Doppler Gestational Age
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Comparable Performance Between Automatic and Manual Laryngeal and Hypopharyngeal Gross Tumor Volume Delineations Validated With Pathology.

International journal of radiation oncology, biology, physics Jan 7, 2025
PURPOSE: Deep learning is a promising approach to increase reproducibility and time-efficiency of gross tumor volume (GTV) delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, ...
Deep Learning Reproducibility of Results Hypopharyngeal Neoplasms Tumor Burden Aged Laryngeal Neoplasms Humans Sensitivity and Specificity Laryngectomy Retrospective Studies Male Female Middle Aged
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Prediction of mortality in intensive care unit with short-term heart rate variability: Machine learning-based analysis of the MIMIC-III database.

Computers in biology and medicine Jan 7, 2025
BACKGROUND: Prognosis prediction in the intensive care unit (ICU) traditionally relied on physiological scoring systems based on clinical indicators at admission. Electrocardiogram (ECG) provides easily accessible information, with heart rate variabi...
Intensive Care Units Female Aged Male Middle Aged Hospital Mortality Electrocardiography Heart Rate Humans Machine Learning Databases, Factual Prognosis Retrospective Studies
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External validation of an artificial intelligence model using clinical variables, including ICD-10 codes, for predicting in-hospital mortality among trauma patients: a multicenter retrospective cohort study.

Scientific reports Jan 7, 2025
Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clini...
Aged Adult Male Middle Aged Cohort Studies Artificial Intelligence Databases, Factual Retrospective Studies Female Hospital Mortality ROC Curve International Classification of Diseases Wounds and Injuries Humans
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CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester.

BMC pregnancy and childbirth Jan 7, 2025
BACKGROUND: Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model...
Humans Artificial Intelligence Retrospective Studies Pregnancy Female Pregnancy Trimester, First Cleft Lip Cleft Palate Reproducibility of Results Adult Ultrasonography, Prenatal Imaging, Three-Dimensional
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The value of multiparametric MRI radiomics and machine learning in predicting preoperative Ki-67 expression level in breast cancer.

BMC medical imaging Jan 7, 2025
OBJECTIVE: This study was to develop a multi-parametric MRI radiomics model to predict preoperative Ki-67 status.
Algorithms Ki-67 Antigen Retrospective Studies Female Multiparametric Magnetic Resonance Imaging Adult Aged Humans Sensitivity and Specificity Machine Learning Breast Neoplasms Radiomics Middle Aged
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