AIMC Topic: Machine Learning

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Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Chemical research in toxicology
Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strategies in the early stages of drug development for human toxicity assessment. At present, artificial in...

Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows.

Sensors (Basel, Switzerland)
Scientific computing heavily relies on data shared by the community, especially in distributed data-intensive applications. This research focuses on predicting slow connections that create bottlenecks in distributed workflows. In this study, we analy...

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Scientific reports
Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swe...

Discovery of senolytics using machine learning.

Nature communications
Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics ...

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning.

Ergonomics
The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using 'BlazePose' with a data set of 50,00...

An enhanced grey wolf optimizer boosted machine learning prediction model for patient-flow prediction.

Computers in biology and medicine
Large and medium-sized general hospitals have adopted artificial intelligence big data systems to optimize the management of medical resources to improve the quality of hospital outpatient services and decrease patient wait times in recent years as a...

Large-Scale Modeling of Sparse Protein Kinase Activity Data.

Journal of chemical information and modeling
Protein kinases are a protein family that plays an important role in several complex diseases such as cancer and cardiovascular and immunological diseases. Protein kinases have conserved ATP binding sites, which when targeted can lead to similar acti...

A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods.

Scientific reports
The problem of missing data, particularly for dichotomous variables, is a common issue in medical research. However, few studies have focused on the imputation methods of dichotomous data and their performance, as well as the applicability of these i...

An end-to-end convolutional neural network for automated failure localisation and characterisation of 3D interconnects.

Scientific reports
The advancement in the field of 3D integration circuit technology leads to new challenges for quality assessment of interconnects such as through silicon vias (TSVs) in terms of automated and time-efficient analysis. In this paper, we develop a fully...

Implementation of artificial intelligence and machine learning-based methods in brain-computer interaction.

Computers in biology and medicine
Brain-computer interfaces are used for direct two-way communication between the human brain and the computer. Brain signals contain valuable information about the mental state and brain activity of the examined subject. However, due to their non-stat...