AIMC Topic: Prognosis

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Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.

Constipation and risk of death and cardiovascular events.

Atherosclerosis
BACKGROUND AND AIMS: Constipation is one of the most frequent symptoms encountered in daily clinical practice and is implicated in the development of atherosclerosis, potentially through altered gut microbiota. However, little is known about its asso...

Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme.

Cancer medicine
BACKGROUND: For Glioblastoma (GBM), various prognostic nomograms have been proposed. This study aims to evaluate machine learning models to predict patients' overall survival (OS) and progression-free survival (PFS) on the basis of clinical, patholog...

On medical application of neural networks trained with various types of data.

Bioscience trends
Neural networks have garnered attention over the past few years. A neural network is a typical model of machine learning that is used to identify visual patterns. Neural networks are used to solve a wide variety of problems, including image recogniti...

PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data.

BMC bioinformatics
BACKGROUND: Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be caused by high complexity of ...

Improving palliative care with deep learning.

BMC medical informatics and decision making
BACKGROUND: Access to palliative care is a key quality metric which most healthcare organizations strive to improve. The primary challenges to increasing palliative care access are a combination of physicians over-estimating patient prognoses, and a ...

Leveraging auxiliary measures: a deep multi-task neural network for predictive modeling in clinical research.

BMC medical informatics and decision making
BACKGROUND: Accurate predictive modeling in clinical research enables effective early intervention that patients are most likely to benefit from. However, due to the complex biological nature of disease progression, capturing the highly non-linear in...