AIMC Topic: Machine Learning

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Development and validation of a machine learning framework for improved resource allocation in the emergency department.

The American journal of emergency medicine
OBJECTIVE: The Emergency Severity Index (ESI) is the most commonly used system in over 70% of all U.S. emergency departments (ED) that uses predicted resource utilization as a means to triage [1], Mistriage, which includes both undertriage and overtr...

Empowering Early Career Neurosurgeons in the Critical Appraisal of Artificial Intelligence and Machine Learning: The Design and Evaluation of a Pilot Course.

World neurosurgery
BACKGROUND: Artificial intelligence (AI) is expected to play a greater role in neurosurgery. There is a need for neurosurgeons capable of critically appraising AI literature to evaluate its implementation or communicate information to patients. Howev...

Machine learning-aided unveiling the relationship between chemical pretreatment and methane production of lignocellulosic waste.

Waste management (New York, N.Y.)
Chemical pretreatment is a common method to enhance the cumulative methane yield (CMY) of lignocellulosic waste (LW) but its effectiveness is subject to various factors, and accurate estimation of methane production of pretreated LW remains a challen...

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

Journal of thrombosis and thrombolysis
This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein thrombosis (DVT) based on patients' limb function, activities of daily living (ADL), clinical laborat...

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

Scientific reports
The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of c...

Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making.

Scientific reports
Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics can be detected. It can be treated if it is detected early. Many artificial intelligence-based models have been developed for skin cancer detection and clas...

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.

Molecular genetics and genomics : MGG
Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-express...

AG-MSTLN-EL: A Multi-source Transfer Learning Approach to Brain Tumor Detection.

Journal of imaging informatics in medicine
The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and diagnose various diseases early. Classifying brain tumors through magnetic resonance imaging (MRI) poses a challenge demanding accurate models for ef...