AIMC Topic: Machine Learning

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Identifying Differences in the Performance of Machine Learning Models for Off-Targets Trained on Publicly Available and Proprietary Data Sets.

Chemical research in toxicology
Each year, publicly available databases are updated with new compounds from different research institutions. Positive experimental outcomes are more likely to be reported; therefore, they account for a considerable fraction of these entries. Establis...

Using machine learning to decode animal communication.

Science (New York, N.Y.)
New methods promise transformative insights and conservation benefits.

Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.

Aging
Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse da...

Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.

Scientific reports
Since the beginning of the COVID-19 pandemic, new and non-invasive digital technologies such as artificial intelligence (AI) had been introduced for mortality prediction of COVID-19 patients. The prognostic performances of the machine learning (ML)-b...

Model-Agnostic Structural Transfer Learning for Cross-Domain Autonomous Activity Recognition.

Sensors (Basel, Switzerland)
Activity recognition using data collected with smart devices such as mobile and wearable sensors has become a critical component of many emerging applications ranging from behavioral medicine to gaming. However, an unprecedented increase in the diver...

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning.

Nature communications
The turnover number k, a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental k estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate comp...

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.

JMIR public health and surveillance
BACKGROUND: Unintentional injury is the leading cause of death in young children. Emergency department (ED) diagnoses are a useful source of information for injury epidemiological surveillance purposes. However, ED data collection systems often use f...

Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.

Journal of biomolecular structure & dynamics
In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science a...

Modeling Epidemiology Data with Machine Learning Technique to Detect Risk Factors for Gastric Cancer.

Journal of gastrointestinal cancer
PURPOSE: Gastric cancer (GC) ranks as the 7th most common cancer worldwide and a leading cause of cancer mortality. In Iran, stomach malignancies are the most common fatal cancers with higher than world average incidence. In recent years, methods lik...