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Brain-based graph-theoretical predictive modeling to map the trajectory of anhedonia, impulsivity, and hypomania from the human functional connectome
Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic...
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Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling
BackgroundMultimorbidity is typically associated with deficient health-related quality of life in mid-life, and the likelihood of develo**...
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Artificial intelligence and machine learning in peritoneal dialysis: a systematic review of clinical outcomes and predictive modeling
BackgroundThe integration of artificial intelligence (AI) and machine learning (ML) in peritoneal dialysis (PD) presents transformative opportunities...
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Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling
Childhood maltreatment (CM) has been associated with changes in structural brain connectivity even in the absence of mental illness. Social support,...
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Just Add Data: automated predictive modeling for knowledge discovery and feature selection
Fully automated machine learning (AutoML) for predictive modeling is becoming a reality, giving rise to a whole new field. We present the basic ideas...
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Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts
BackgroundSARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae...
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Predictive modeling of perioperative patient deterioration: combining unanticipated ICU admissions and mortality for improved risk prediction
ObjectiveThis paper presents a comprehensive analysis of perioperative patient deterioration by develo** predictive models that evaluate...
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Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies
Purpose of ReviewFamilial hypercholesterolemia (FH) is a hereditary condition characterized by elevated levels of low-density lipoprotein cholesterol...
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Risk stratification and predictive modeling of postoperative delirium in chronic subdural hematoma
Background — Postoperative delirium is a common complication associated with the elderly, causing increased morbidity and prolonged hospital stay....
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Radiomics predictive modeling from dual-time-point FDG PET Ki parametric maps: application to chemotherapy response in lymphoma
BackgroundTo investigate the use of dynamic radiomics features derived from dual-time-point (DTP-feature) [ 18 F]FDG PET metabolic uptake rate K i ...
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A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data
BackgroundSurvival prediction using high-dimensional molecular data is a hot topic in the field of genomics and precision medicine, especially for...
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Molecular subty** and the construction of a predictive model of colorectal cancer based on ion channel genes
PurposeColorectal cancer (CRC) is a highly heterogeneous malignancy with an unfavorable prognosis. The purpose of this study was to address the...
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Predictive modeling for COVID-19 readmission risk using machine learning algorithms
IntroductionThe COVID-19 pandemic overwhelmed healthcare systems with severe shortages in hospital resources such as ICU beds, specialized doctors,...
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Predictive modeling of postoperative gastrointestinal dysfunction: the role of serum bilirubin, sodium levels, and surgical duration in gynecological cancer care
ObjectiveTo elucidate the role of preoperative serum bilirubin and sodium levels, along with the duration of surgery, in predicting postoperative...
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Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling
Disruptions in frontoparietal networks supporting emotion regulation have been long implicated in maladaptive childhood aggression. However, the...
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Building a predictive model of low birth weight in low- and middle-income countries: a prospective cohort study
BackgroundLow birth weight (LBW, < 2500 g) infants are at significant risk for death and disability. Improving outcomes for LBW infants requires...
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Incidence, risk factors, and predictive modeling of stoma site incisional hernia after enterostomy closure: a multicenter retrospective cohort study
PurposeStoma site incisional hernia (SSIH) is a common complication, but its incidence and risk factors are not well known. The objective of this...
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Predictive modeling for the germline pathogenic variant of the APC gene in patients with adenomatous polyposis: proposing a new APC score
BackgroundThe precise diagnosis and medical management of patients with suspected familial adenomatous polyposis should be based on genetic testing,...
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Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach
BackgroundAcute kidney injury (AKI) is one of the preventable complications of percutaneous coronary intervention (PCI). This study aimed to develop...
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Predictive performance of radiomic models based on features extracted from pretrained deep networks
ObjectivesIn radiomics, generic texture and morphological features are often used for modeling. Recently, features extracted from pretrained deep...
