AIMC Topic: Disease-Free Survival

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Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

Journal of cancer research and clinical oncology Aug 27, 2020
PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI...
Neovascularization, Pathologic Microcirculation Cohort Studies Liver Neoplasms Carcinoma, Hepatocellular Models, Statistical Disease-Free Survival Humans Retrospective Studies Female Male Middle Aged Deep Learning
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Development of a Machine Learning Model for Survival Risk Stratification of Patients With Advanced Oral Cancer.

JAMA network open Aug 3, 2020
IMPORTANCE: A tool for precisely stratifying postoperative patients with advanced oral cancer is crucial for the treatment plan, such as intensifying or deintensifying the regimen to improve their quality of life and prognosis.
Humans Machine Learning Prognosis Risk Assessment Mouth Neoplasms Disease-Free Survival Chemoradiotherapy, Adjuvant Retrospective Studies Kaplan-Meier Estimate Female Adult Male Middle Aged
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Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept.

Scientific reports Jul 23, 2020
Sepsis is the primary cause of burn-related mortality and morbidity. Traditional indicators of sepsis exhibit poor performance when used in this unique population due to their underlying hypermetabolic and inflammatory response following burn injury....
Humans Machine Learning Databases, Factual Female Adult Predictive Value of Tests Burns Models, Biological Disease-Free Survival Survival Rate Male Middle Aged Sepsis Age Factors
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: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer.

Scientific reports Jul 23, 2020
Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account....
Humans Lung Neoplasms Predictive Value of Tests Disease-Free Survival Positron-Emission Tomography Aged, 80 and over Databases, Factual Survival Rate Tomography, X-Ray Computed Male Female Middle Aged Aged Deep Learning
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A machine learning-based prognostic predictor for stage III colon cancer.

Scientific reports Jun 25, 2020
Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis ...
Humans Colon Young Adult Follow-Up Studies Female Machine Learning Disease-Free Survival Adult Neoplasm Staging Prognosis Risk Factors Image Interpretation, Computer-Assisted Male Aged Neoplasm Recurrence, Local Colectomy Middle Aged Aged, 80 and over Colonic Neoplasms Kaplan-Meier Estimate Risk Assessment
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Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

European radiology Jun 10, 2020
OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).
Disease-Free Survival Tumor Burden Fluorodeoxyglucose F18 Kaplan-Meier Estimate Middle Aged Diagnosis, Computer-Assisted Deep Learning Glycolysis Treatment Outcome Squamous Cell Carcinoma of Head and Neck Predictive Value of Tests Aged Positron Emission Tomography Computed Tomography Aged, 80 and over Neoplasm Staging Adult Mouth Neoplasms Algorithms Sensitivity and Specificity Retrospective Studies Male Female Reproducibility of Results Humans
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Identification of a novel gene signature for the prediction of recurrence in HCC patients by machine learning of genome-wide databases.

Scientific reports Mar 10, 2020
Hepatocellular carcinoma (HCC) is a common malignant tumor in China. In the present study, we aimed to construct and verify a prediction model of recurrence in HCC patients using databases (TCGA, AMC and Inserm) and machine learning methods and obtai...
Biomarkers, Tumor Gene Expression Profiling Liver Neoplasms Carcinoma, Hepatocellular Gene Expression Regulation, Neoplastic Neoplasm Recurrence, Local Humans Disease-Free Survival Machine Learning Survival Rate
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Artificial intelligence-guided tissue analysis combined with immune infiltrate assessment predicts stage III colon cancer outcomes in PETACC08 study.

Gut Nov 28, 2019
OBJECTIVE: Diagnostic tests, such as Immunoscore, predict prognosis in patients with colon cancer. However, additional prognostic markers could be detected on pathological slides using artificial intelligence tools.
Artificial Intelligence Prognosis Antineoplastic Combined Chemotherapy Protocols Adenocarcinoma Lymphocytes, Tumor-Infiltrating Humans Neoplasm Invasiveness Neoplasm Staging Colonic Neoplasms Disease-Free Survival Image Interpretation, Computer-Assisted
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A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BMC genomics Nov 13, 2019
BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation, transcriptional regulation, post-transcriptional regulation and other aspects, thus participating ...
Disease-Free Survival Kaplan-Meier Estimate Adenocarcinoma Support Vector Machine RNA, Long Noncoding Microsatellite Instability Humans Prognosis Stomach Neoplasms Cohort Studies Models, Genetic
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A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PloS one Oct 2, 2019
PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features.
Keratins, Hair-Specific Carcinoma, Pancreatic Ductal Antineoplastic Combined Chemotherapy Protocols Keratins, Type II Adult Disease-Free Survival Oxaliplatin Leucovorin Survival Rate Deoxycytidine Pancreatic Neoplasms Humans Sensitivity and Specificity Gemcitabine Neoplasm Proteins Machine Learning Male Irinotecan Fluorouracil Retrospective Studies Middle Aged Female
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