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Construct Machine Learning Models to Predict the Recurrence Probability of Patients with Hepatocellular Carcinoma

https://doi.org/10.2139/ssrn.4756041
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Computed tomography for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease
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Magnetic resonance imaging for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease
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Magnetic resonance imaging for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease
inferredcites →https://doi.org/10.1002/hep.29913openalex-extracted
Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases
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The efficacy of transarterial chemoembolization in downstaging unresectable hepatocellular carcinoma to curative therapy: a predicted regression model
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Models to Predict Development or Recurence of Hepatocellular Carcinoma (HCC) in Patients with Advanced Hepatic Fibrosis
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Machine Learning for Hypertension Prediction: a Systematic Review
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Goals and targets for personalized therapy for HCC
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Interplay between inflammation and cancer
inferredcites →https://doi.org/10.1016/j.acra.2023.09.008openalex-extracted
Radiomics-based Machine Learning to Predict the Recurrence of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis
inferredcites →https://doi.org/10.1016/j.ajodo.2023.08.003openalex-extracted
Support vector machines
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From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
inferredcites →https://doi.org/10.1016/j.csbj.2021.09.001openalex-extracted
Machine learning and deep learning methods that use omics data for metastasis prediction
inferredcites →https://doi.org/10.1016/j.jceh.2022.06.009openalex-extracted
Artificial Intelligence in Hepatology- Ready for the Primetime
inferredcites →https://doi.org/10.1016/j.jhep.2009.07.009openalex-extracted
Risk factors for early and late recurrence in hepatitis B-related hepatocellular carcinoma
inferredcites →https://doi.org/10.1016/j.jhepr.2022.100557openalex-extracted
The ALBI score: From liver function in patients with HCC to a general measure of liver function
inferredcites →https://doi.org/10.1016/s0140-6736(22)01200-4openalex-extracted
Hepatocellular carcinoma
inferredcites →https://doi.org/10.1016/s1470-2045(14)70263-3openalex-extracted
Cancer-related inflammation and treatment effectiveness
inferredcites →https://doi.org/10.1084/jem.20181739openalex-extracted
Modulating inflammation for cancer therapy
inferredcites →https://doi.org/10.1097/ppo.0000000000000684openalex-extracted
Hepatocellular Carcinoma—Southeast Asia Updates
inferredcites →https://doi.org/10.1152/ajpheart.00497.2021openalex-extracted
Ensemble machine learning model identifies patients with HFpEF from matrix-related plasma biomarkers
inferredcites →https://doi.org/10.1177/0962280215626466openalex-extracted
A review of statistical updating methods for clinical prediction models
inferredcites →https://doi.org/10.1177/1073274817744621openalex-extracted
Liver Resection and Surgical Strategies for Management of Primary Liver Cancer
inferredcites →https://doi.org/10.1186/s12859-022-04657-3openalex-extracted
Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system
inferredcites →https://doi.org/10.1186/s12885-021-07969-4openalex-extracted
Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion
inferredcites →https://doi.org/10.1186/s12885-023-10620-zopenalex-extracted
CT texture analysis in predicting treatment response and survival in patients with hepatocellular carcinoma treated with transarterial chemoembolization using random forest models
inferredcites →https://doi.org/10.1186/s12935-020-01274-zopenalex-extracted
Random-forest algorithm based biomarkers in predicting prognosis in the patients with hepatocellular carcinoma
inferredcites →https://doi.org/10.1186/s13073-021-00968-xopenalex-extracted
Deep learning in cancer diagnosis, prognosis and treatment selection
inferredcites →https://doi.org/10.1200/jco.2012.41.5984openalex-extracted
Prognostic Nomogram for Intrahepatic Cholangiocarcinoma After Partial Hepatectomy
inferredcites →https://doi.org/10.1213/ane.0000000000005247openalex-extracted
Logistic Regression in Medical Research
inferredcites →https://doi.org/10.1245/s10434-012-2513-1openalex-extracted
A Systematic Review of Microvascular Invasion in Hepatocellular Carcinoma: Diagnostic and Prognostic Variability
inferredcites →https://doi.org/10.12659/aot.934924openalex-extracted
Recurrence of Hepatocellular Carcinoma After Liver Transplantation: Risk Factors and Predictive Models
inferredcites →https://doi.org/10.1308/147870804290openalex-extracted
Artificial intelligence in medicine
inferredcites →https://doi.org/10.1515/cclm-2022-0291openalex-extracted
Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis
inferredcites →https://doi.org/10.21037/atm.2019.08.63openalex-extracted
In-depth mining of clinical data: the construction of clinical prediction model with R
inferredcites →https://doi.org/10.2147/cmar.s190545openalex-extracted
The prognostic and predictive value of the combination of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in patients with hepatocellular carcinoma who receive transarterial chemoembolization therapy
inferredcites →https://doi.org/10.2174/1381612826666200331091156openalex-extracted
Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis
inferredcites →https://doi.org/10.2174/1574892818666221018091415openalex-extracted
Prediction of Cancer Treatment Using Advancements in Machine Learning
inferredcites →https://doi.org/10.21873/cgp.20063openalex-extracted
Applications of Support Vector Machine (SVM) Learning in Cancer Genomics
inferredcites →https://doi.org/10.3322/caac.21660openalex-extracted
Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries
inferredcites →https://doi.org/10.3389/fendo.2022.946915openalex-extracted
Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy
inferredcites →https://doi.org/10.3390/cancers13112830openalex-extracted
Neutrophil-to-Lymphocyte Ratio as a Biomarker Predicting Overall Survival after Chemoembolization for Intermediate-Stage Hepatocellular Carcinoma
inferredcites →https://doi.org/10.3724/zdxbyxb-2022-0569openalex-extracted
Application of artificial neural network algorithm in pathological diagnosis and prognosis prediction of digestive tract malignant tumors
inferredcites →https://doi.org/10.3748/wjg.v29.i8.1243openalex-extracted
Predictors of early and late hepatocellular carcinoma recurrence
inferredcites →https://doi.org/10.5582/bst.2021.01094openalex-extracted
Surgical treatment of hepatocellular carcinoma
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