AIMC Topic: Algorithms

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Water quality parameters retrieval and nutrient status evaluation based on machine learning methods and Sentinel- 2 imagery: a case study of the Hongjiannao Lake.

Environmental monitoring and assessment
A timely and accurate understanding of lake water quality is significant for maintaining ecological balance, ensuring water resource security, and promoting regional sustainable development. However, due to the varying numerical ranges and characteri...

Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm.

European journal of medical research
OBJECTIVES: This study aims to develop a reliable and interpretable predictive model for long-term survival in Type A aortic dissection (TAAD) patients, utilizing machine learning (ML) algorithms.

Optimization of CO absorption into MDEA-PZ-sulfolane hybrid solution using machine learning algorithms and RSM.

Environmental science and pollution research international
This study presents the modeling and simulation of carbon dioxide (CO₂) absorption in hybrid amine solutions using machine learning algorithms and response surface methodology (RSM). The process was governed by adjustable input parameters, including ...

Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.

Frontiers in cellular and infection microbiology
OBJECTIVE: Metagenomic next-generation sequencing (mNGS) can potentially detect various pathogenic microorganisms without bias to improve the diagnostic rate of fever of unknown origin (FUO), but there are no effective methods to predict mNGS-positiv...

Multi-scale prototype convolutional network for few-shot semantic segmentation.

PloS one
Few-shot semantic segmentation aims to accurately segment objects from a limited amount of annotated data, a task complicated by intra-class variations and prototype representation challenges. To address these issues, we propose the Multi-Scale Proto...

Tracking control of robotic manipulator end-effector trajectory based on robust sliding mode method.

PloS one
This paper addresses the precise trajectory tracking of robotic manipulators (RMs) in automation tasks, particularly in hazardous environments. A dynamic model of the end-effector in Cartesian coordinates is developed to represent the system's motion...

Saturation transfer MR fingerprinting for magnetization transfer contrast and chemical exchange saturation transfer quantification.

Magnetic resonance in medicine
PURPOSE: The aim of this study was to develop a saturation transfer MR fingerprinting (ST-MRF) technique using a biophysics model-driven deep learning approach.

Using pathology images and artificial intelligence to identify bacterial infections and their types.

Journal of microbiological methods
Bacterial infections pose a significant biosafety concern, making early and accurate diagnosis essential for effective treatment and prognosis. Traditional diagnostic methods, while reliable, are often slow and fail to meet urgent clinical demands. I...

Utilizing Pix2Pix conditional generative adversarial networks to recover missing data in preclinical PET scanner sinogram gaps.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: The presence of a gap between adjacent detector blocks in Positron Emission Tomography (PET) scanners introduces a partial loss of projection data, which can degrade the image quality and quantitative accuracy of reconstructed PET images....