AIMC Topic: Prognosis

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Introduction to The Spine Journal special issue on artificial intelligence and machine learning.

The spine journal : official journal of the North American Spine Society
In the last 5 years, artificial intelligence (AI) algorithms have made rapid advances for diagnosis and prognosis in fields ranging from dermatology to anesthesiology. How do we make sense of the rise of AI in healthcare and specifically in spine? Ho...

Artificial neural networks for multi-omics classifications of hepato-pancreato-biliary cancers: towards the clinical application of genetic data.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Several multi-omics classifications have been proposed for hepato-pancreato-biliary (HPB) cancers, but these classifications have not proven their role in the clinical practice and been validated in external cohorts.

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Scientific reports
Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have been adapted for this task. Although they have shown to yield results at least as good as classical met...

[Artificial intelligence in psychiatry: predictive value of characteristics on MR imaging of the brain].

Nederlands tijdschrift voor geneeskunde
The clinical application of neuroimaging for psychological complaints has so far been limited to the exclusion of somatic pathology. Radiological assessment of brain scans usually does not explain the psychological symptoms. However, that does not me...

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.

Nature communications
Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which use...

Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer.

Molecular imaging and biology
PURPOSE: To examine the prognostic significance of pretreatment 2-deoxy-2-[F]fluoro-D-glucose ([F]-FDG) positron emission tomography (PET)-based radiomic features using a machine learning approach in patients with endometrial cancers.

Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.

The Lancet. Digital health
BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with COVID-19. We aimed to develop and evaluate an artificial intelligence system using chest x-rays and ...

A machine learning-based survival prediction model of high grade glioma by integration of clinical and dose-volume histogram parameters.

Cancer medicine
PURPOSE: Glioma is the most common type of primary brain tumor in adults, and it causes significant morbidity and mortality, especially in high-grade glioma (HGG) patients. The accurate prognostic prediction of HGG is vital and helpful for clinicians...

Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BMC pulmonary medicine
BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretati...

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer.

Scientific reports
This study addresses the core issue facing a surgical team during breast cancer surgery: quantitative prediction of tumor likelihood including estimates of prediction error. We have previously reported that a molecular probe, Laser Raman spectroscopy...