AIMC Topic: Prognosis

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Deep learning for the dynamic prediction of multivariate longitudinal and survival data.

Statistics in medicine
The joint model for longitudinal and survival data improves time-to-event predictions by including longitudinal outcome variables in addition to baseline covariates. However, in practice, joint models may be limited by parametric assumptions in both ...

Prognosis patients with COVID-19 using deep learning.

BMC medical informatics and decision making
BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensi...

A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer.

Journal of cancer research and clinical oncology
PURPOSE: Most of Stage II/III colorectal cancer (CRC) patients can be cured by surgery alone, and only certain CRC patients benefit from adjuvant chemotherapy. Risk stratification based on deep-learning from haematoxylin and eosin (H&E) images has be...

A Deep Learning Radiomics Analysis for Survival Prediction in Esophageal Cancer.

Journal of healthcare engineering
The purpose of this study was to explore the deep learning radiomics (DLR) nomogram to predict the overall 3-year survival after chemoradiotherapy in patients with esophageal cancer. The 154 patients' data were used in this study, which was randomly ...

Test Strategy Optimization Based on Soft Sensing and Ensemble Belief Measurement.

Sensors (Basel, Switzerland)
Resulting from the short production cycle and rapid design technology development, traditional prognostic and health management (PHM) approaches become impractical and fail to match the requirement of systems with structural and functional complexity...

Using Artificial Intelligence to Better Predict and Develop Biomarkers.

Heart failure clinics
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, tr...

Continence definition and prognostic factors for early urinary continence recovery in posterior rhabdosphincter reconstruction after robot-assisted radical prostatectomy. Post-hoc analysis of a randomised controlled trial.

Actas urologicas espanolas
INTRODUCTION: Urinary incontinence after radical prostatectomy (RP) is an adverse event with high impact on patient's quality of life. Nowadays there is no standardized method for urinary continence measurement. Posterior rhabdosphincter reconstructi...

Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer.

Current oncology (Toronto, Ont.)
Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early detection and diagnosis, comprehensive assessment of treatment response, and precise prediction of prognosis are essential to improve the patients' survival rate. In ...

Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning.

Oxidative medicine and cellular longevity
BACKGROUND: Ovarian cancer (OC) is a malignancy exhibiting high mortality in female tumors. Glycosylation is a posttranslational modification of proteins but research has failed to demonstrate a systematic link between glycosylation-related signature...

Advances in computed tomography-based prognostic methods for intracerebral hemorrhage.

Neurosurgical review
Spontaneous intracerebral hemorrhage (ICH) has high morbidity and mortality. Computed tomography (CT) plays an important role in the diagnosis, treatment, and research of cerebrovascular diseases. Non-contrast CT is widely used in the clinical diagno...