AIMC Topic: Retrospective Studies

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CT-Based Body Composition Measures and Systemic Disease: A Population-Level Analysis Using Artificial Intelligence Tools in Over 100,000 Patients.

AJR. American journal of roentgenology Jan 8, 2025
CT-based abdominal body composition measures have shown associations with important health outcomes. Advances in artificial intelligence (AI) now allow deployment of tools that measure body composition in large patient populations. The purpose of t...
Humans Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Middle Aged Body Composition Female Aged Adult Male
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Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.

AJR. American journal of roentgenology Jan 8, 2025
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...
Spinal Fractures Missed Diagnosis Tomography, X-Ray Computed Female Aged Adult Diagnostic Errors Male Middle Aged Radiologists Cervical Vertebrae Humans Machine Learning Retrospective Studies
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Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer.

Gut and liver Jan 8, 2025
BACKGROUND/AIMS: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predict...
Neoplasm Staging Aged Aged, 80 and over Colorectal Neoplasms Male Middle Aged ROC Curve Lymph Nodes Lymphatic Metastasis Predictive Value of Tests Humans Artificial Intelligence Algorithms Retrospective Studies Female
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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 Patient Admission Decision Support Techniques Databases, Factual Hyperglycemia Chronic Disease Middle Aged Predictive Value of Tests Risk Assessment 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 Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Diffusion Magnetic Resonance Imaging Humans Retrospective Studies Female Aged 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 Immunotherapy Carcinoma, Non-Small-Cell Lung Pneumonia Combined Modality Therapy Aged Male Middle Aged Deep Learning Radiation Pneumonitis Humans Retrospective Studies Tomography, X-Ray Computed Female
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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 Logistic Models Support Vector Machine Retrospective Studies Intensive Care Units Female Risk Factors Aged Humans Machine Learning Algorithms Prognosis
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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, ...
Hypopharyngeal Neoplasms Deep Learning Reproducibility of Results Tumor Burden Aged Laryngeal Neoplasms Sensitivity and Specificity Laryngectomy Male Middle Aged Humans Retrospective Studies Female
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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...
Heart Rate Humans Machine Learning Databases, Factual Male Middle Aged Hospital Mortality Electrocardiography Prognosis Retrospective Studies Intensive Care Units Female Aged
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