AIMC Topic: Algorithms

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Think deep in the tractography game: deep learning for tractography computing and analysis.

Brain structure & function
Tractography is a challenging process with complex rules, driving continuous algorithmic evolution to address its challenges. Meanwhile, deep learning has tackled similarly difficult tasks, such as mastering the Go board game and animating sophistica...

Characterization of m6A-Related Genes in Tumor-Associated Macrophages for Prognosis, Immunotherapy, and Drug Prediction in Lung Adenocarcinomas Based on Machine Learning Algorithms.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Tumor-associated macrophages (TAMs) are a vital immune component within the tumor microenvironment (TME) of lung adenocarcinoma (LUAD), exerting significant influence on tumor growth, metastasis, and drug resistance. N6-methyladenosine (m6A) modifica...

The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review.

Journal of medical Internet research
BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...

Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.

Biomedical physics & engineering express
: Effective lung gas exchange relies on the balance between alveolar ventilation and perfusion, which can be disrupted in mechanically ventilated patients. Lung perfusion assessment using electrical impedance tomography (EIT) typically involves a sud...

[Acoustic technology empowers the diagnosis and treatment of respiratory diseases: challenges, and prospects].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Respiratory diseases is a major challenge to global public health. In recent years, acoustic technology has shown great potential as a non-invasive and convenient diagnostic method for detecting and monitoring respiratory diseases. With the developme...

The fluorescence spectrum combined with a broad learning system to characterize the content of difenoconazole in cabbage.

Analytical methods : advancing methods and applications
Pesticide residue detection plays an important role in vegetable quality and food safety. In this work, we propose a method for detecting difenoconazole pesticide residues based on fluorescence spectroscopy technology and machine learning algorithms....

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Mesenteric malperfusion (MMP) is an uncommon but devastating complication of acute aortic dissection (AAD) that combines 2 life-threatening conditions-aortic dissection and acute mesenteric ischemia. The complex pathophysiology of MMP pos...

Artificial intelligence and endoanal ultrasound: pioneering automated differentiation of benign anal and sphincter lesions.

Techniques in coloproctology
BACKGROUND: Anal injuries, such as lacerations and fissures, are challenging to diagnose because of their anatomical complexity. Endoanal ultrasound (EAUS) has proven to be a reliable tool for detailed visualization of anal structures but relies on e...

SMVSNN: An Intelligent Framework for Anticancer Drug-Drug Interaction Prediction Utilizing Spiking Multi-view Siamese Neural Networks.

Journal of chemical information and modeling
The study of synergistic drug combinations is vital in cancer treatment, enhancing efficacy, reducing resistance, and minimizing side effects through complementary drug actions. Drug-drug interaction (DDI) analysis offers essential theoretical suppor...

Machine Learning Pipeline for Molecular Property Prediction Using ChemXploreML.

Journal of chemical information and modeling
We present ChemXploreML, a modular desktop application designed for machine learning-based molecular property prediction. The framework's flexible architecture allows integration of any molecular embedding technique with modern machine learning algor...