AIMC Topic: Machine Learning

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Computational methods to automate the initial interpretation of lower extremity arterial Doppler and duplex carotid ultrasound studies.

Journal of vascular surgery
BACKGROUND: Lower extremity arterial Doppler (LEAD) and duplex carotid ultrasound studies are used for the initial evaluation of peripheral arterial disease and carotid stenosis. However, intra- and inter-laboratory variability exists between interpr...

Artificial intelligence in drug discovery: recent advances and future perspectives.

Expert opinion on drug discovery
: Artificial intelligence (AI) has inspired computer-aided drug discovery. The widespread adoption of machine learning, in particular deep learning, in multiple scientific disciplines, and the advances in computing hardware and software, among other ...

Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.

World neurosurgery
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...

Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

The International journal of eating disorders
OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to ...

Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion.

Journal of chemical information and modeling
Combinatorial fusion analysis (CFA) is an approach for combining multiple scoring systems using the rank-score characteristic function and cognitive diversity measure. One example is to combine diverse machine learning models to achieve better predic...

Deep Transfer Learning Approach for Automatic Recognition of Drug Toxicity and Inhibition of SARS-CoV-2.

Viruses
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes COVID-19 and is responsible for the ongoing pandemic. Screening of potential antiviral drugs against SARS-CoV-2 depend on in vitro experiments, which are based on the quantification ...

Iterative guided machine learning-assisted systematic literature reviews: a diabetes case study.

Systematic reviews
BACKGROUND: Systematic Reviews (SR), studies of studies, use a formal process to evaluate the quality of scientific literature and determine ensuing effectiveness from qualifying articles to establish consensus findings around a hypothesis. Their val...

Local-Global Memory Neural Network for Medication Prediction.

IEEE transactions on neural networks and learning systems
Electronic medical records (EMRs) play an important role in medical data mining and sequential data learning. In this article, we propose to use a sequential neural network with dynamic content-based memories to predict future medications, given EMRs...

A Survey on Learning-Based Approaches for Modeling and Classification of Human-Machine Dialog Systems.

IEEE transactions on neural networks and learning systems
With the rapid development from traditional machine learning (ML) to deep learning (DL) and reinforcement learning (RL), dialog system equipped with learning mechanism has become the most effective solution to address human-machine interaction proble...