AIMC Topic: Machine Learning

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Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems.

Journal of chemical theory and computation
Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD simulations are ...

Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy.

Epilepsia
OBJECTIVE: Improving the identification of the epileptogenic zone and associated seizure-spreading regions represents a significant challenge. Innovative brain-imaging modalities tracking neurovascular dynamics during seizures may provide new disease...

On the Unfounded Enthusiasm for Soft Selective Sweeps III: The Supervised Machine Learning Algorithm That Isn't.

Genes
In the last 15 years or so, soft selective sweep mechanisms have been catapulted from a curiosity of little evolutionary importance to a ubiquitous mechanism claimed to explain most adaptive evolution and, in some cases, most evolution. This transfor...

Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study.

Reproductive biology and endocrinology : RB&E
BACKGROUND: To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to imp...

Successful incorporation of single reviewer assessments during systematic review screening: development and validation of sensitivity and work-saved of an algorithm that considers exclusion criteria and count.

Systematic reviews
BACKGROUND: Accepted systematic review (SR) methodology requires citation screening by two reviewers to maximise retrieval of eligible studies. We hypothesized that records could be excluded by a single reviewer without loss of sensitivity in two con...

Machine learning-based investigation of the cancer protein secretory pathway.

PLoS computational biology
Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is ofte...

Longitudinal self-supervised learning.

Medical image analysis
Machine learning analysis of longitudinal neuroimaging data is typically based on supervised learning, which requires large number of ground-truth labels to be informative. As ground-truth labels are often missing or expensive to obtain in neuroscien...

Basic of machine learning and deep learning in imaging for medical physicists.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The manuscript aims at providing an overview of the published algorithms/automation tool for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed using the query string to identify the proposed approaches (algorith...

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning.

Sensors (Basel, Switzerland)
After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in ...

Application of machine learning techniques to physical and rehabilitative medicine.

Annali di igiene : medicina preventiva e di comunita
Nowadays, digital information has increased exponentially in every field to such an extent that it generates huge amounts of electronic data, namely Big Data. In the field of Artificial Intelligence, Machine Learning can be exploited in order to tran...