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Logistic Models

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Dynamic Data Infrastructure Security for Interoperable e-Healthcare Systems: A Semantic Feature-Driven NoSQL Intrusion Attack Detection Model.

BioMed research international
The exponential rise in advanced software computing and low-cost hardware has broadened the horizon for the Internet of Medical Things (IoMT), interoperable e-Healthcare systems serving varied purposes including electronic healthcare records (EHRs) a...

An artificial intelligence-based risk prediction model of myocardial infarction.

BMC bioinformatics
BACKGROUND: Myocardial infarction can lead to malignant arrhythmia, heart failure, and sudden death. Clinical studies have shown that early identification of and timely intervention for acute MI can significantly reduce mortality. The traditional MI ...

Characteristic Analysis and Route Optimization of Heterogeneous Neural Network in Logistics Allocation System.

Computational intelligence and neuroscience
Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the increasing diversification of urban industrial and commercial development mode, the optimal scheduling o...

Integrated Learning Model-Based Assessment of Enteral Nutrition Support in Neurosurgical Intensive Care Patients.

BioMed research international
To observe the clinical efficacy of early enteral nutrition application in critically ill neurosurgical patients, in this paper, we have developed a prediction model for enteral nutrition support in neurosurgical intensive care patients which is prim...

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study.

BMC neurology
BACKGROUNDS: We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.

Survival Prediction After Neurosurgical Resection of Brain Metastases: A Machine Learning Approach.

Neurosurgery
BACKGROUND: Current prognostic models for brain metastases (BMs) have been constructed and validated almost entirely with data from patients receiving up-front radiotherapy, leaving uncertainty about surgical patients.

Using machine learning techniques to predict antimicrobial resistance in stone disease patients.

World journal of urology
PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This study aims to offer an evaluation of the performance of machine learning (ML) techniques, for predictin...

Development of a deep learning model that predicts Bi-level positive airway pressure failure.

Scientific reports
Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated with harm. The objective of this study was to develop a deep learning model capable of aiding clinical decision making by predicting Bi-Level Positiv...

Predicting risks of low birth weight in Bangladesh with machine learning.

PloS one
BACKGROUND AND OBJECTIVE: Low birth weight is one of the primary causes of child mortality and several diseases of future life in developing countries, especially in Southern Asia. The main objective of this study is to determine the risk factors of ...

Construction of Enterprise Financial Early Warning Model Based on Logistic Regression and BP Neural Network.

Computational intelligence and neuroscience
At present, the number of enterprises in financial crisis in China is rising sharply, and the ability of enterprises to resist risks is generally weak. Therefore, it is necessary to establish a corporate financial crisis early warning system, to dete...