AIMC Topic: Machine Learning

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Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence.

JCO precision oncology
PURPOSE: Endometrial cancer (EC) is the most common gynecologic cancer in the United States with rising incidence and mortality. Despite optimal treatment, 15%-20% of all patients will recur. To better select patients for adjuvant therapy, it is impo...

Replacing non-biomedical concepts improves embedding of biomedical concepts.

PloS one
Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. Traditional biomedical embedding techniques often replace all synonymous words representing biologic...

Exploring the drivers of digital transformation in Chinese port and shipping enterprises: A machine learning approach.

PloS one
With the transition to a global green low-carbon economy, the urgency for digital transformation in the port and shipping industry has become increasingly prominent in making enterprises more efficient and sustainable. This study focuses on how Chine...

Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.

American journal of Alzheimer's disease and other dementias
To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a...

Prediction of high-risk pregnancy based on machine learning algorithms.

Scientific reports
This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. The study is based on the maternal ...

Histidine-engineered Cu-BTC nanozyme with enhanced laccase-like activity combining the machine learning for precise recognition of Beta-lactam antibiotics.

Biosensors & bioelectronics
Although nanozyme sensor arrays can simultaneously recognize multiple target substances, they are currently rarely used for identifying Beta-lactam antibiotics (BLs). This may be due to the lower catalytic performance of some nanozymes in practical a...

A novel method for achieving ecological indicator based on vertical soil bacterial communities coupled with machine learning: A case study of a typical tropical site in China.

Journal of hazardous materials
Global industrialization has resulted in severe contamination of soil with heavy metals (HMs). Nevertheless, it is unclear if it affects the depth-resolved bacterial communities. Herein, we collected soil samples at different depths from a typical HM...

Identifying emergency department patients at high risk for opioid overdose using natural language processing and machine learning.

Journal of substance use and addiction treatment
INTRODUCTION: Emergency departments (ED) are potential sites for identifying and treating individuals at high risk for opioid overdose. This study used machine learning (ML)-based models to predict opioid overdose death in the 12 months after an ED v...

Delving into transfer learning within U-Net for refined retinal vessel segmentation: An extensive hyperparameter analysis.

Photodiagnosis and photodynamic therapy
Blood vessel segmentation poses numerous challenges. Firstly, blood vessels often lack sufficient contrast against the background, impeding accurate differentiation. Additionally, the overlapping nature of blood vessels complicates separating individ...

Determining the biomarkers and pathogenesis of myocardial infarction combined with ankylosing spondylitis via a systems biology approach.

Frontiers of medicine
Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). However, research dedicated to elucidating the pathogenesis of AS-MI is lacking. In this study, we explored the biomarkers for enhancing the diagnostic an...