AIMC Topic: Machine Learning

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Ovarian torsion: developing a machine-learned algorithm for diagnosis.

Pediatric radiology
BACKGROUND: Ovarian torsion is a common concern in girls presenting to emergency care with pelvic or abdominal pain. The diagnosis is challenging to make accurately and quickly, relying on a combination of physical exam, history and radiologic evalua...

Identifying epilepsy psychiatric comorbidities with machine learning.

Acta neurologica Scandinavica
OBJECTIVE: People with epilepsy are at increased risk for mental health comorbidities. Machine-learning methods based on spoken language can detect suicidality in adults. This study's purpose was to use spoken words to create machine-learning classif...

Next-generation drug repurposing using human genetics and network biology.

Current opinion in pharmacology
Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatmen...

Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap.

Clinical pharmacology and therapeutics
Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real-world data from electronic heal...

A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

Scientific reports
High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncover...

Measuring the diffusion of innovations with paragraph vector topic models.

PloS one
Measuring the diffusion of innovations from textual data sources besides patent data has not been studied extensively. However, early and accurate indicators of innovation and the recognition of trends in innovation are mandatory to successfully prom...

Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Artificial intelligence in medicine
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...

A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network.

Sensors (Basel, Switzerland)
Increasing grain production is essential to those areas where food is scarce. Increasing grain production by controlling crop diseases and pests in time should be effective. To construct video detection system for plant diseases and pests, and to bui...

Structural Analysis and Optimization of Convolutional Neural Networks with a Small Sample Size.

Scientific reports
Deep neural networks have gained immense popularity in the Big Data problem; however, the availability of training samples can be relatively limited in specific application domains, particularly medical imaging, and consequently leading to overfittin...