AIMC Topic: Machine Learning

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An integrated approach of feature selection and machine learning for early detection of breast cancer.

Scientific reports
Breast cancer ranks among the most prevalent cancers in women globally, with its treatment efficacy heavily reliant on the early identification and diagnosis of the disease. The importance of early detection and diagnosis cannot be overstated in enha...

Water quality parameters retrieval and nutrient status evaluation based on machine learning methods and Sentinel- 2 imagery: a case study of the Hongjiannao Lake.

Environmental monitoring and assessment
A timely and accurate understanding of lake water quality is significant for maintaining ecological balance, ensuring water resource security, and promoting regional sustainable development. However, due to the varying numerical ranges and characteri...

Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm.

European journal of medical research
OBJECTIVES: This study aims to develop a reliable and interpretable predictive model for long-term survival in Type A aortic dissection (TAAD) patients, utilizing machine learning (ML) algorithms.

Optimization of CO absorption into MDEA-PZ-sulfolane hybrid solution using machine learning algorithms and RSM.

Environmental science and pollution research international
This study presents the modeling and simulation of carbon dioxide (CO₂) absorption in hybrid amine solutions using machine learning algorithms and response surface methodology (RSM). The process was governed by adjustable input parameters, including ...

Identification of aging-related biomarkers for intervertebral disc degeneration in whole blood samples based on bioinformatics and machine learning.

Frontiers in immunology
INTRODUCTION: Aging is characterized by gradual structural and functional changes in the body over time, with intervertebral disc degeneration (IVDD) representing a key manifestation of spinal aging and a major contributor to low back pain (LBP).

Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.

Frontiers in cellular and infection microbiology
OBJECTIVE: Metagenomic next-generation sequencing (mNGS) can potentially detect various pathogenic microorganisms without bias to improve the diagnostic rate of fever of unknown origin (FUO), but there are no effective methods to predict mNGS-positiv...

Population-level individualized prospective prediction of opioid overdose using machine learning.

Molecular psychiatry
The opioid overdose epidemic has rapidly expanded in North America, with rates accelerating during the COVID-19 pandemic. No existing study has demonstrated prospective opioid overdose at a population level. This study aimed to develop and validate a...

Predicting Maximal Military Occupational Task Performance from Physical Fitness Tests Using Machine Learning.

Medicine and science in sports and exercise
PURPOSE: Optimal performance in military tasks is crucial for operational success. These tasks are often simulated in training, assessing personnel performance within a military environment. However, these assessments are time-consuming and a potenti...