AIMC Topic: Severity of Illness Index

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A hybrid inception-dilated-ResNet architecture for deep learning-based prediction of COVID-19 severity.

Scientific reports Feb 22, 2025
Chest computed tomography (CT) scans are essential for accurately assessing the severity of the novel Coronavirus (COVID-19), facilitating appropriate therapeutic interventions and monitoring disease progression. However, determining COVID-19 severit...
Male Lung Severity of Illness Index Deep Learning COVID-19 Tomography, X-Ray Computed Female SARS-CoV-2 Humans Neural Networks, Computer
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Machine learning and computational fluid dynamics derived FFRCT demonstrate comparable diagnostic performance in patients with coronary artery disease; A Systematic Review and Meta-Analysis.

Journal of cardiovascular computed tomography Feb 22, 2025
BACKGROUND: As a new noninvasive diagnostic technique, computed tomography-derived fraction flow reserve (FFRCT) has been used to identify hemodynamically significant coronary artery stenosis. FFRCT can be calculated using computational fluid dynamic...
Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Reproducibility of Results Models, Cardiovascular Fractional Flow Reserve, Myocardial Coronary Artery Disease Coronary Stenosis Coronary Vessels Hydrodynamics Computed Tomography Angiography
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Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions Feb 21, 2025
BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses mac...
Humans Machine Learning Retrospective Studies Female Reproducibility of Results Aged Male Middle Aged Image Interpretation, Computer-Assisted Percutaneous Coronary Intervention Observer Variation Automation Severity of Illness Index Coronary Artery Disease Coronary Vessels Treatment Outcome Prosthesis Design Predictive Value of Tests Stents Ultrasonography, Interventional
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Improving reliability of movement assessment in Parkinson's disease using computer vision-based automated severity estimation.

Journal of Parkinson's disease Feb 13, 2025
BackgroundClinical assessments of motor symptoms rely on observations and subjective judgments against standardized scales, leading to variability due to confounders. Improving inter-rater agreement is essential for effective disease management.Objec...
Parkinson Disease Video Recording Movement Prospective Studies Neurologic Examination Female Humans Reproducibility of Results Aged Machine Learning Male Middle Aged Severity of Illness Index
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Applying machine learning to ecological momentary assessment data to identify predictors of loss-of-control eating and overeating severity in adolescents: A preliminary investigation.

Appetite Feb 6, 2025
OBJECTIVE: Several factors (e.g., interpersonal stress, affect) predict loss-of-control (LOC) eating and overeating in adolescents, but most past research has tested predictors separately. We applied machine learning to simultaneously evaluate multip...
Feeding Behavior Craving Ecological Momentary Assessment Hyperphagia Humans Machine Learning Severity of Illness Index Adolescent Stress, Psychological Adolescent Behavior Female Male
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Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation.

PloS one Feb 6, 2025
This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural language processing (NLP) applications. After the model creation, we applied the resulting model, LastBER...
Humans Attention Deficit Disorder with Hyperactivity Severity of Illness Index Social Media Natural Language Processing
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Deep learning radiomics nomogram for preoperatively identifying moderate-to-severe chronic cholangitis in children with pancreaticobiliary maljunction: a multicenter study.

BMC medical imaging Feb 5, 2025
BACKGROUND: Long-term severe cholangitis can lead to dense adhesions and increased fragility of the bile duct, complicating surgical procedures and elevating operative risk in children with pancreaticobiliary maljunction (PBM). Consequently, preopera...
Humans Retrospective Studies Tomography, X-Ray Computed Female Deep Learning Adolescent Child, Preschool Child Nomograms Radiomics Male Infant Severity of Illness Index Chronic Disease Cholangitis Pancreaticobiliary Maljunction
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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

Journal of cardiovascular computed tomography Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Coronary Angiography Coronary Artery Disease Coronary Vessels Reproducibility of Results Vascular Calcification Risk Factors Aged Machine Learning Male Humans Decision Support Techniques Severity of Illness Index Prognosis Adipose Tissue Middle Aged Female Predictive Value of Tests Risk Assessment
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A machine learning model using clinical notes to estimate PHQ-9 symptom severity scores in depressed patients.

Journal of affective disorders Feb 3, 2025
BACKGROUND: Lack of widespread use of the Patient Health Questionnaire 9-item (PHQ-9) in clinical practice inhibits measurement of treatment follow-up for patients with major depressive disorder (MDD). This study developed, validated and applied a ma...
Humans Male Middle Aged Depressive Disorder, Major Severity of Illness Index Patient Health Questionnaire Machine Learning Electronic Health Records Female Adult
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Risk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy.

BMC pregnancy and childbirth Jan 30, 2025
BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) is a liver disorder that occurs in the second and third trimesters of pregnancy and is associated with a significant risk of fetal complications, including premature birth and fetal death. In cl...
Pregnancy Complications Pregnancy Humans Severity of Illness Index Neural Networks, Computer Female Case-Control Studies Machine Learning Risk Factors China Adult Cholestasis, Intrahepatic
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