AIMC Topic: Machine Learning

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Multi-label classification with XGBoost for metabolic pathway prediction.

BMC bioinformatics
BACKGROUND: Metabolic pathway prediction is one possible approach to address the problem in system biology of reconstructing an organism's metabolic network from its genome sequence. Recently there have been developments in machine learning-based pat...

Is Novelty Predictable?

Cold Spring Harbor perspectives in biology
Machine learning-based design has gained traction in the sciences, most notably in the design of small molecules, materials, and proteins, with societal applications ranging from drug development and plastic degradation to carbon sequestration. When ...

Benford's Law and distributions for better drug design.

Expert opinion on drug discovery
INTRODUCTION: Modern drug discovery incorporates various tools and data, heralding the beginning of the data-driven drug design (DD) era. The distributions of chemical and physical data used for Artificial Intelligence (AI)/Machine Learning (ML) and ...

The use of machine learning in paediatric nutrition.

Current opinion in clinical nutrition and metabolic care
PURPOSE OF REVIEW: In recent years, there has been a burgeoning interest in using machine learning methods. This has been accompanied by an expansion in the availability and ease of use of machine learning tools and an increase in the number of large...

Methodology for Good Machine Learning with Multi-Omics Data.

Clinical pharmacology and therapeutics
In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4-year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio-ge...

RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci.

Genome biology
Expansions of tandem repeats (TRs) cause approximately 60 monogenic diseases. We expect that the discovery of additional pathogenic repeat expansions will narrow the diagnostic gap in many diseases. A growing number of TR expansions are being identif...

A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat.

Journal of computer-aided molecular design
An important aspect in the development of small molecules as drugs or agrochemicals is their systemic availability after intravenous and oral administration. The prediction of the systemic availability from the chemical structure of a potential candi...

Ultrasound tomography enhancement by signal feature extraction with modular machine learning method.

PloS one
Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography. The key idea is to analyze the time-dependent ultrasonic sig...

A comprehensive review on artificial intelligence in water treatment for optimization. Clean water now and the future.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Given the severe effects that toxic compounds present in wastewater streams have on humans, it is imperative that water and wastewater streams pollution be addressed globally. This review comprehensively examines various water and wastewater treatmen...

Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions.

Journal of environmental sciences (China)
The presence of aluminum (Al) and fluoride (F) ions in the environment can be harmful to ecosystems and human health, highlighting the need for accurate and efficient monitoring. In this paper, an innovative approach is presented that leverages the p...