AIMC Topic: Machine Learning

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Meta-tuning and fast optimization of machine learning models for dynamic methane prediction in anaerobic digestion.

Bioresource technology
This study evaluates the performance of several optimization algorithms for tuning a data preparation and hyperparameter optimization pipeline applied to machine and deep learning models predicting methane production. Bayesian ridge regression and re...

Supervised machine learning and molecular docking modeling to identify potential Anti-Parkinson's agents.

Journal of molecular graphics & modelling
Parkinson's disease is a neurodegenerative condition that affects the brain's neurons, and causes malfunction of nerve cells and their death. A neurotransmitter called dopamine interacts with the part of the brain in charge of coordination and moveme...

Assessing the impact of low-temperature stress during anthesis stage on winter wheat grain development through computer vision and machine learning.

Journal of the science of food and agriculture
BACKGROUND: Extreme weather events, particularly spring low-temperature stress exacerbated by global warming, have become increasingly prevalent in the Huang-Huai-Hai Basin over the past 40 years, a key wheat-producing area in China. This study aims ...

Interpretable inverse iteration mean shift networks for clustering tasks.

Neural networks : the official journal of the International Neural Network Society
Neural networks have become the standard approach for tasks such as computer vision, machine translation and pattern recognition. While they exhibit significant feature representation capabilities, they often lack interpretability. This suggests that...

FedPPD: Towards effective subgraph federated learning via pseudo prototype distillation.

Neural networks : the official journal of the International Neural Network Society
Subgraph federated learning (subgraph-FL) is a distributed machine learning paradigm enabling cross-client collaborative training of graph neural networks (GNNs). However, real-world subgraph-FL scenarios often face subgraph heterogeneity problem, i....

A pipeline for enabling Nearshore Infrared Video Super-resolution to learn more high-frequency foreground information.

Neural networks : the official journal of the International Neural Network Society
A key challenge in Nearshore Infrared Video Super-resolution (NIVSR) is the limited high-frequency foreground information. The most common approach is to fuse frames in order to learn cross-temporal information. However, existing methods struggle to ...

Towards the next generation of species delimitation methods: an overview of machine learning applications.

Molecular phylogenetics and evolution
Species delimitation is the process of distinguishing between populations of the same species and distinct species of a particular group of organisms. Various methods exist for inferring species limits, whether based on morphological, molecular, or o...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

International journal of medical informatics
BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifestyle habits. Early identification of at-risk individuals through machine learning models-based approac...

Improved two-view interactional fuzzy learning based on mutual-rectification and knowledge-mergence.

Neural networks : the official journal of the International Neural Network Society
Nasopharyngeal carcinoma (NPC) is a malignant tumor that originates from the back of the nasal canal from above the soft palate to the upper larynx. Because the nasopharyngeal location is deeply hidden, it is often difficult for a single imaging mean...

Identification of Npas4 as a biomarker for CICI by transcriptomics combined with bioinformatics and machine learning approaches.

Experimental neurology
Chemotherapy is one of the most successful strategies for treating cancer. Unfortunately, up to 70 % of cancer survivors develop cognitive impairment during or after chemotherapy, which severely affects their quality of life. We first established a m...