AIMC Topic: Machine Learning

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A novel lncRNA-protein interaction prediction method based on deep forest with cascade forest structure.

Scientific reports
Long noncoding RNAs (lncRNAs) regulate many biological processes by interacting with corresponding RNA-binding proteins. The identification of lncRNA-protein Interactions (LPIs) is significantly important to well characterize the biological functions...

Prediction of blood supply in vestibular schwannomas using radiomics machine learning classifiers.

Scientific reports
This study attempts to explore the radiomics-based features of multi-parametric magnetic resonance imaging (MRI) and construct a machine-learning model to predict the blood supply in vestibular schwannoma preoperatively. By retrospectively collecting...

Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation.

Scientific reports
Critically ill patients affected by atrial fibrillation are at high risk of adverse events: however, the actual risk stratification models for haemorrhagic and thrombotic events are not validated in a critical care setting. With this paper we aimed t...

Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors.

Scientific reports
Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of indiv...

Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach.

Nature communications
Assisted reproductive technologies (ART) are increasingly used, however little is known about the long-term health of ART-conceived offspring. Weak selection of comparison groups and poorly characterized mechanisms impede current understanding. In a ...

Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention.

Computational intelligence and neuroscience
To unlock information present in clinical description, automatic medical text classification is highly useful in the arena of natural language processing (NLP). For medical text classification tasks, machine learning techniques seem to be quite effec...

Comparing classification models-a practical tutorial.

Journal of computer-aided molecular design
While machine learning models have become a mainstay in Cheminformatics, the field has yet to agree on standards for model evaluation and comparison. In many cases, authors compare methods by performing multiple folds of cross-validation and reportin...

Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter.

NeuroImage
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur...

Efficient and targeted COVID-19 border testing via reinforcement learning.

Nature
Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all travellers to restricting ent...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

PLoS computational biology
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...