AIMC Topic: Retrospective Studies

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Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.

International journal of cardiology Dec 18, 2024
BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and some...
Contrast Media Aged Cardiomyopathy, Hypertrophic Adult Gadolinium Male Magnetic Resonance Imaging, Cine Middle Aged Humans Cohort Studies Machine Learning Retrospective Studies Female
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Improving the prediction of patient survival with the aid of residual convolutional neural network (ResNet) in colorectal cancer with unresectable liver metastases treated with bevacizumab-based chemotherapy.

Cancer imaging : the official publication of the International Cancer Imaging Society Dec 18, 2024
BACKGROUND: To verify overall survival predictions made with residual convolutional neural network-determined morphological response (ResNet-MR) in patients with unresectable synchronous liver-only metastatic colorectal cancer (mCRC) treated with bev...
Middle Aged Liver Neoplasms Antineoplastic Combined Chemotherapy Protocols Humans Fluorouracil Aged Neural Networks, Computer Bevacizumab Adult Retrospective Studies Colorectal Neoplasms Tomography, X-Ray Computed Male Female
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Combined inflammation-related biomarkers and clinicopathological features for the prognosis of stage II/III colorectal cancer by machine learning.

BMC cancer Dec 18, 2024
BACKGROUND: Inflammation-related biomarkers, such as systemic inflammation score (SIS) and neutrophil-lymphocyte ratio (NLR), are associated with colorectal cancer prognosis. However, the combined role of SIS, NLR, and clinicopathological factors in ...
Neoplasm Staging Lymphocytes Lymphocyte Count Middle Aged Inflammation Nomograms Neutrophils Female Humans Aged Machine Learning Colorectal Neoplasms Prognosis Biomarkers, Tumor Retrospective Studies Male
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Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

BMC infectious diseases Dec 18, 2024
BACKGROUND: During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identi...
COVID-19 Retrospective Studies Female SARS-CoV-2 Risk Factors Humans Adolescent Aged Machine Learning Child, Preschool Aged, 80 and over Child Young Adult COVID-19 Nucleic Acid Testing Adult Male Middle Aged Infant China
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Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department.

BMC emergency medicine Dec 18, 2024
BACKGROUND: Accurate triage is required for efficient allocation of resources and to decrease patients' length of stay. Triage decisions are often subjective and vary by provider, leading to patients being over-triaged or under-triaged. This study de...
Machine Learning Retrospective Studies Emergency Service, Hospital Female Aged Adult Male Humans Middle Aged China Triage Natural Language Processing
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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Cardiovascular diabetology Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Cause of Death Stroke Triglycerides Blood Glucose Time Factors Hospital Mortality Predictive Value of Tests Female Reproducibility of Results Risk Factors Aged Male Middle Aged Risk Assessment China Length of Stay Biomarkers Prognosis Retrospective Studies Critical Illness Intensive Care Units Humans Machine Learning Databases, Factual
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Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BMC medical informatics and decision making Dec 18, 2024
BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management.
Humans Machine Learning Adult Male Middle Aged Blood Transfusion Critical Care Retrospective Studies Intensive Care Units Female Aged Netherlands
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A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms.

BMC medical informatics and decision making Dec 18, 2024
BACKGROUND: Aplastic anemia (AA) and myelodysplastic neoplasms (MDS) have similar peripheral blood manifestations and are clinically characterized by reduced hematological triad. It is challenging to distinguish and diagnose these two diseases. Hence...
Middle Aged Anemia, Aplastic Myelodysplastic Syndromes Retrospective Studies Female Aged Aged, 80 and over Male Humans Machine Learning Algorithms
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Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.

BMC nephrology Dec 18, 2024
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
Support Vector Machine Kidney Neoplasms Carcinoma, Renal Cell Nephrectomy Middle Aged Postoperative Complications Disease Progression Renal Insufficiency, Chronic Humans Machine Learning Retrospective Studies Female Aged Male
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Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.

BMC psychiatry Dec 18, 2024
OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disability rates, which are timely imperative to identify and intervene in clinical practice. The objective of this study was to explore the association betwe...
Middle Aged Humans Depression Support Vector Machine Heart Rate Depressive Disorder Machine Learning Retrospective Studies Female Adult Male
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