AIMC Topic: Machine Learning

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Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.

Journal of thoracic imaging
PURPOSE: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.

Frontiers in immunology
BACKGROUND: The "gut-skin axis" has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have constructed an interpretable machine learning framework to quantitatively screen key gut flora.

The application of machine learning in clinical microbiology and infectious diseases.

Frontiers in cellular and infection microbiology
With the development of artificial intelligence(AI) in computer science and statistics, it has been further applied to the medical field. These applications include the management of infectious diseases, in which machine learning has created inroads ...

Simultaneous determination of pesticide residues and rapid discrimination of corn production origin using ambient ionization mass spectrometry combined with machine learning.

Food chemistry
Food traceability is a critical aspect of quality control and food safety. In this study, a high-throughput analysis system with an analysis time of 13 min was developed for the detection of pesticide residues in corn, achieving low limits of detecti...

The emerging role of second harmonic generation/two photon excitation for precision digital analysis of liver fibrosis in MASH clinical trials.

Journal of hepatology
Conventional histopathological evaluation of liver biopsy slides has been invaluable in assessing the causes of liver injury, the severity of the underlying disease processes, and the degree of resulting fibrosis. However, the use of conventional his...

An artificial intelligence interpretable tool to predict risk of deep vein thrombosis after endovenous thermal ablation.

Journal of vascular surgery. Venous and lymphatic disorders
OBJECTIVE: Endovenous thermal ablation (EVTA) stands as one of the primary treatments for superficial venous insufficiency. Concern exists about the potential for thromboembolic complications following this procedure. Although rare, those complicatio...

On neural architecture search and hyperparameter optimization: A max-flow based approach.

Neural networks : the official journal of the International Neural Network Society
Automated Machine Learning (AutoML) involves the automatic production of models for specific tasks on given datasets, which can be divided into two aspects: Neural Architecture Search (NAS) for model construction and Hyperparameter Optimization (HPO)...

The future of HIV diagnostics: an exemplar in infectious diseases.

The lancet. HIV
Over the past 40 years, diagnostics have become the backbone of HIV prevention, treatment, and retention in care, and are central to the achievement of UNAIDS 95-95-95 targets. Over the next decade, the global HIV response will face difficult challen...

Standardizing a microbiome pipeline for body fluid identification from complex crime scene stains.

Applied and environmental microbiology
Recent advances in next-generation sequencing have opened up new possibilities for applying the human microbiome in various fields, including forensics. Researchers have capitalized on the site-specific microbial communities found in different parts ...

Unveiling PFAS hazard in European surface waters using an interpretable machine-learning model.

Environment international
Per- and polyfluoroalkyl substances (PFAS), commonly known as "forever chemicals", are ubiquitous in surface waters and potentially threaten human health and ecosystems. Despite extensive monitoring efforts, PFAS risk in European surface waters remai...