AIMC Topic: Proportional Hazards Models

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Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms.

PloS one
We investigate a new method to place patients into risk groups in censored survival data. Properties such as median survival time, and end survival rate, are implicitly improved by optimizing the area under the survival curve. Artificial neural netwo...

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Annals of surgical oncology
BACKGROUND: The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, convent...

Robotic-assisted pelvic lymph node dissection for prostate cancer: frequency of nodal metastases and oncological outcomes.

World journal of urology
PURPOSE: Limited data are available regarding the oncologic efficacy of pelvic lymph node dissection (PLND) performed during robotic-assisted laparoscopic prostatectomy (RALP) for prostate cancer. We aimed to determine the frequency of pelvic lymph n...

UGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits.

Heredity
Biological outcomes are governed by multiple genetic and environmental factors that act in concert. Determining multifactor interactions is the primary topic of interest in recent genetics studies but presents enormous statistical and mathematical ch...

Prognostication in patients with idiopathic pulmonary fibrosis using quantitative airway analysis from HRCT: a retrospective study.

The European respiratory journal
BACKGROUND: Predicting shorter life expectancy is crucial for prioritising antifibrotic therapy in fibrotic lung diseases (FLDs), where progression varies widely, from stability to rapid deterioration. This heterogeneity complicates treatment decisio...

Quantitative Computed Tomography Measures of Lung Fibrosis and Outcomes in the National Lung Screening Trial.

Annals of the American Thoracic Society
Incidental features of interstitial lung disease (ILD) are commonly observed on chest computed tomography (CT) scans and are independently associated with poor outcomes. Although most studies to date have relied on qualitative assessments of ILD, qu...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a co...

CCTA-Derived coronary plaque burden offers enhanced prognostic value over CAC scoring in suspected CAD patients.

European heart journal. Cardiovascular Imaging
AIMS: To assess the prognostic utility of coronary artery calcium (CAC) scoring and coronary computed tomography angiography (CCTA)-derived quantitative plaque metrics for predicting adverse cardiovascular outcomes.