AIMC Topic: Prognosis

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Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database.

The Lancet. Digital health
BACKGROUND: Accurate prognostication is crucial in treatment decisions made for men diagnosed with non-metastatic prostate cancer. Current models rely on prespecified variables, which limits their performance. We aimed to investigate a novel machine ...

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

PloS one
The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus, initially identified in Wuhan (Hubei province, China) and currently spreading across six continents causing a considerable harm to patients, with no ...

Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning.

Ophthalmology. Retina
PURPOSE: To evaluate the predictive usefulness of quantitative imaging biomarkers, acquired automatically from OCT scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-...

Machine learning predictive model for severe COVID-19.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
To develop a modified predictive model for severe COVID-19 in people infected with Sars-Cov-2. We developed the predictive model for severe patients of COVID-19 based on the clinical date from the Tumor Center of Union Hospital affiliated with Tongji...

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients.

Nature communications
The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from ...

EffiCare: Better Prognostic Models via Resource-Efficient Health Embeddings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Recent medical prognostic models adapted from high data-resource fields like language processing have quickly grown in complexity and size. However, since medical data typically constitute low data-resource settings, performances on tasks like clinic...

An Interpretable Machine Learning Survival Model for Predicting Long-term Kidney Outcomes in IgA Nephropathy.

AMIA ... Annual Symposium proceedings. AMIA Symposium
IgA nephropathy (IgAN) is common worldwide and has heterogeneous phenotypes. Predicting long-term outcomes is important for clinical decision-making. As right-censored patients become common during the long-term follow-up, either excluding these pati...

Association of AI quantified COVID-19 chest CT and patient outcome.

International journal of computer assisted radiology and surgery
PURPOSE: Severity scoring is a key step in managing patients with COVID-19 pneumonia. However, manual quantitative analysis by radiologists is a time-consuming task, while qualitative evaluation may be fast but highly subjective. This study aims to d...

A Machine Learning-Based Investigation of Gender-Specific Prognosis of Lung Cancers.

Medicina (Kaunas, Lithuania)
BACKGROUND AND OBJECTIVE: Primary lung cancer is a lethal and rapidly-developing cancer type and is one of the most leading causes of cancer deaths.