AIMC Topic: Algorithms

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A novel method of combining generalized frequency response function and convolutional neural network for complex system fault diagnosis.

PloS one
To solve the problem of low accuracy in traditional fault diagnosis methods, a novel method of combining generalized frequency response function(GFRF) and convolutional neural network(CNN) is proposed. In order to accurately characterize system state...

A Comparison between Mouse, , and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking.

eNeuro
Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential min...

Prediction of stenosis behaviour in artery by neural network and multiple linear regressions.

Biomechanics and modeling in mechanobiology
Blood flow analysis in the artery is a paramount study in the field of arterial stenosis evaluation. Studies conducted so far have reported the analysis of blood flow parameters using different techniques, but the regression analysis is not adequatel...

Unpaired Multi-Modal Segmentation via Knowledge Distillation.

IEEE transactions on medical imaging
Multi-modal learning is typically performed with network architectures containing modality-specific layers and shared layers, utilizing co-registered images of different modalities. We propose a novel learning scheme for unpaired cross-modality image...

Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.

Cancer cytopathology
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspiration biopsy (FNAB). Each category has an associated risk of malignancy, which is important in the ...

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enough blood to meet the needs of...

Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

International journal of molecular sciences
Untargeted metabolomics may become a standard approach to address diagnostic requests, but, at present, data interpretation is very labor-intensive. To facilitate its implementation in metabolic diagnostic screening, we developed a method for automat...

Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches.

International journal of molecular sciences
A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with...

Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.

IEEE journal of biomedical and health informatics
OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machine learning based systems can aid in automatically screening patients, the robustness of these syste...