AIMC Topic: Algorithms

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Deep Learning-Based Fully Automated Aortic Valve Leaflets and Root Measurement From Computed Tomography Images - A Feasibility Study.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: The aim of this study was to retrain our existing deep learning-based fully automated aortic valve leaflets/root measurement algorithm, using computed tomography (CT) data for root dilatation (RD), and assess its clinical feasibility.

Novel natural vector with asymmetric covariance for classifying biological sequences.

Gene
The genome sequences of organisms form a large and complex landscape, presenting a significant challenge in bioinformatics: how to utilize mathematical tools to describe and analyze this space effectively. The ability to compare relationships between...

Diagnostic report generation for macular diseases by natural language processing algorithms.

The British journal of ophthalmology
AIMS: To investigate rule-based and deep learning (DL)-based methods for the automatically generating natural language diagnostic reports for macular diseases.

Digital Butterworth filter as preprocessing method for implementing Raman spectroscopy as an analytical method in downstream processing of biopharmaceuticals.

Journal of chromatography. A
For implementing Raman spectroscopy as an analytical method in downstream processing, extracting molecular information related to biopharmaceuticals is still challenging due to spectral variations caused by spectrometer, setup and fluorescence. This ...

Temporal evolution stages classification and aging time prediction of gel-pen ink using GC-IMS combined with machine learning for forensic science applications.

Journal of chromatography. A
Determining the temporal evolution of inks remains a critical challenge in forensic document analysis. The temporal evolution stages classification and aging time prediction of gel-pen ink were investigated by integrating gas chromatography-ion mobil...

An efficient and precise (micro)plastic identification method: feature infrared spectra extraction based on EIS-VIP-CARS and ANN modeling.

Environmental research
Understanding microplastics' (MPs) ecological impact necessitates their precise identification. To address the issue of the competitive adaptive reweighted sampling (CARS) algorithm extracting numerous feature wavenumber points (FWPs) that often miss...

A novel hybrid machine learning approach for accurate retrieval of ocean surface chlorophyll-a across oligotrophic to eutrophic waters.

Environmental research
Accurate assessment of chlorophyll a (Chla) concentration distribution and variations is significant for environmental monitoring and ecological research. However, the inversion of Chla in different optical types of water bodies can only be achieved ...

A Meta-Learning Approach for Multicenter and Small-Data Single-Cell Image Analysis.

Analytical chemistry
The application of algorithm-based single-cell imaging techniques can visualize and analyze cellular heterogeneity. However, algorithm-based single-cell imaging techniques are severely limited by the high workload required to label single-cell images...

Applied Machine Learning for Prediction of Energy-Efficient CO Desorption on Solid Acid Catalysts.

Environmental science & technology
The development of solid acid catalysts (SACs) for energy-efficient CO desorption and amine regeneration is critical to carbon capture commercialization. To avoid the time-consuming and ineffective screening process, a predictive model correlating th...

Reconstructing Super-Resolution Raman Spectral Image Using a Generative Adversarial Network-Based Algorithm.

Analytical chemistry
Raman imaging utilizes molecular fingerprint information to visualize the spatial distribution of a substance within the scanned area. Subject to its scanning mechanism, it usually costs a prolonged data acquisition duration for achieving high-resolu...