AIMC Topic: Machine Learning

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Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses.

Journal of chemical information and modeling
Machine learning scoring functions for protein-ligand binding affinity have been found to consistently outperform classical scoring functions when trained and tested on crystal structures of bound protein-ligand complexes. However, it is less clear h...

Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study.

The Lancet. Digital health
BACKGROUND: Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic screening services. We, therefore, aimed to develop and evaluate a machine learning-based screening te...

Learning offline: memory replay in biological and artificial reinforcement learning.

Trends in neurosciences
Learning to act in an environment to maximise rewards is among the brain's key functions. This process has often been conceptualised within the framework of reinforcement learning, which has also gained prominence in machine learning and artificial i...

Relation extraction from DailyMed structured product labels by optimally combining crowd, experts and machines.

Journal of biomedical informatics
The effectiveness of machine learning models to provide accurate and consistent results in drug discovery and clinical decision support is strongly dependent on the quality of the data used. However, substantive amounts of open data that drive drug d...

Revisiting performance metrics for prediction with rare outcomes.

Statistical methods in medical research
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under ...

A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques.

Expert review of medical devices
INTRODUCTION: Researchers and engineers have found their importance in healthcare industry including recent updates in patient-specific implant (PSI) design. CAD/CAM technology plays an important role in the design and development of Artificial Intel...

Visual Analytics for Hypothesis-Driven Exploration in Computational Pathology.

IEEE transactions on visualization and computer graphics
Recent advances in computational and algorithmic power are evolving the field of medical imaging rapidly. In cancer research, many new directions are sought to characterize patients with additional imaging features derived from radiology and patholog...

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.

Journal of chemical theory and computation
Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing mach...

Enhanced Changeover Detection in Industry 4.0 Environments with Machine Learning.

Sensors (Basel, Switzerland)
Changeover times are an important element when evaluating the Overall Equipment Effectiveness (OEE) of a production machine. The article presents a machine learning (ML) approach that is based on an external sensor setup to automatically detect chang...

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.

Scientific reports
Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bacterial 16S marker gene but have not reported the metabolic function of the gut microbiome, which may ...