AIMC Topic: Logistic Models

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Machine learning to predict the cancer-specific mortality of patients with primary non-metastatic invasive breast cancer.

Surgery today
PURPOSE: We used five machine-learning algorithms to predict cancer-specific mortality after surgical resection of primary non-metastatic invasive breast cancer.

The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.

The Journal of surgical research
BACKGROUND: Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal he...

Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study.

BMC medical research methodology
BACKGROUND: Interest in models for calculating the risk of death in traumatic patients admitted to ICUs remains high. These models use variables derived from the deviation of physiological parameters and/or the severity of anatomical lesions with res...

Machine Learning to Develop and Internally Validate a Predictive Model for Post-operative Delirium in a Prospective, Observational Clinical Cohort Study of Older Surgical Patients.

Journal of general internal medicine
BACKGROUND: Our objective was to assess the performance of machine learning methods to predict post-operative delirium using a prospective clinical cohort.

Predicting the consequences of accidents involving dangerous substances using machine learning.

Ecotoxicology and environmental safety
A new dimension of learning lessons from the occurrence of hazardous events involving dangerous substances is considered relying on the availability of representative data and the significant evolution of a wide range of machine learning tools. The i...

Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network.

International journal of environmental research and public health
A better understanding of circumstances contributing to the severity outcome of traffic crashes is an important goal of road safety studies. An in-depth crash injury severity analysis is vital for the proactive implementation of appropriate mitigatio...

Machine learning based early warning system enables accurate mortality risk prediction for COVID-19.

Nature communications
Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk predict...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

Journal of the American College of Surgeons
BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascular, trauma, and orthopaedic surgery have rendered the sensitivity of this score obsolete. A significant number of patients receive amputation during ...

Metabolic pathway inference using multi-label classification with rich pathway features.

PLoS computational biology
Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at different levels of biological organization. A common method for determining the metabolic potential encod...

Robust edge-based biomarker discovery improves prediction of breast cancer metastasis.

BMC bioinformatics
BACKGROUND: The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metastasis. Recently there is a surging interest in combining gene expression with gene networks such as p...