AIMC Topic: Prognosis

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Four transcription profile-based models identify novel prognostic signatures in oesophageal cancer.

Journal of cellular and molecular medicine
Oesophageal cancer (ESCA) is a clinically challenging disease with poor prognosis and health-related quality of life. Here, we investigated the transcriptome of ESCA to identify high risk-related signatures. A total of 159 ESCA patients of The Cancer...

Gene expression based survival prediction for cancer patients-A topic modeling approach.

PloS one
Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard ...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BMC genomics
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 ...

Machine Learning-Based Prediction Models for 30-Day Readmission after Hospitalization for Chronic Obstructive Pulmonary Disease.

COPD
While machine learning approaches can enhance prediction ability, little is known about their ability to predict 30-day readmission after hospitalization for Chronic Obstructive Pulmonary Disease (COPD). We identified patients aged ≥40 years with unp...

Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model.

Scientific reports
The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered...

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma.

BMC medical informatics and decision making
BACKGROUND: Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models have achieved state-of-the-a...