AIMC Topic: Machine Learning

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A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R.

Multivariate behavioral research
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection ...

Development and multicenter validation of machine learning models for predicting postoperative pulmonary complications after neurosurgery.

Chinese medical journal
BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery.

Emerging applications of fluorescence excitation-emission matrix with machine learning for water quality monitoring: A systematic review.

Water research
Fluorescence excitation-emission matrix (FEEM) spectroscopy is increasingly utilized in water quality monitoring due to its rapid, sensitive, and non-destructive measurement capabilities. The integration of machine learning (ML) techniques with FEEM ...

Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches.

International journal of medical informatics
OBJECTIVES: While prior machine learning (ML) models for cancer survivability prediction often treated all cancer stages uniformly, cancer survivability prediction should involve understanding how different stages impact the outcomes. Additionally, t...

A Perspective on Artificial Intelligence for Molecular Pathologists.

The Journal of molecular diagnostics : JMD
The widespread adoption of next-generation sequencing technology in molecular pathology has enabled us to interrogate the genome as never before. The huge quantities of data generated by sequencing, the enormous complexity of human and microbial gene...

Prognostic Implications of Machine Learning Algorithm-Supported Diagnostic Classification of Myocardial Injury Using the Fourth Universal Definition of Myocardial Infarction.

Heart, lung & circulation
BACKGROUND: With widespread adoption of high-sensitivity troponin assays, more individuals with myocardial injury are now identified, with type 1 myocardial infarction (T1MI) being less common despite having the most well-established evidence base to...

Intelligent decoding platform for peptide sequences: SERS detection via high affinity self-assembled silver nanoparticles and machine learning analysis.

Analytica chimica acta
BACKGROUND: Peptides are compounds formed by the dehydration-condensation reaction of two or more amino acids which play an important role in the life functions of the organism. Changes in the structure of amino acids and peptides are vital for eluci...

Automated pediatric TMJ articular disk identification and displacement classification in MRI with machine learning.

Journal of dentistry
OBJECTIVE: To evaluate the performance of an automated two-step model interpreting pediatric temporomandibular joint (TMJ) magnetic resonance imaging (MRI) using artificial intelligence (AI). Using deep learning techniques, the model first automatica...

PhageDPO: A machine-learning based computational framework for identifying phage depolymerases.

Computers in biology and medicine
Bacteriophages (phages) are the most predominant and genetically diverse biological entities on Earth. Phages are viruses that infect bacteria and encode numerous proteins with potential biotechnological application. However, most phage-encoded prote...

Detection of brain tumors using a transfer learning-based optimized ResNet152 model in MR images.

Computers in biology and medicine
Brain tumors are incredibly harmful and can drastically reduce life expectancy. Most researchers use magnetic resonance (MR) scans to detect tumors because they can provide detailed images of the affected area. Recently, AI-based deep learning method...