AI Medical Compendium Topic

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Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...

Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction.

Artificial intelligence in medicine
OBJECTIVE: The use of artificial intelligence techniques to find out which Single Nucleotide Polymorphisms (SNPs) promote the development of a disease is one of the features of medical research, as such techniques may potentially aid early diagnosis ...

Construction accident narrative classification: An evaluation of text mining techniques.

Accident; analysis and prevention
Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classi...

A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...

Photorealistic Monocular Gaze Redirection Using Machine Learning.

IEEE transactions on pattern analysis and machine intelligence
We propose a general approach to the gaze redirection problem in images that utilizes machine learning. The idea is to learn to re-synthesize images by training on pairs of images with known disparities between gaze directions. We show that such lear...

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual ...

Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...

Automatic feed phase identification in multivariate bioprocess profiles by sequential binary classification.

Analytica chimica acta
In this paper, we propose a new strategy for retrospective identification of feed phases from online sensor-data enriched feed profiles of an Escherichia Coli (E. coli) fed-batch fermentation process. In contrast to conventional (static), data-driven...

Development of machine learning models for diagnosis of glaucoma.

PloS one
The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features fro...

Quad-phased data mining modeling for dementia diagnosis.

BMC medical informatics and decision making
BACKGROUND: The number of people with dementia is increasing along with people's ageing trend worldwide. Therefore, there are various researches to improve a dementia diagnosis process in the field of computer-aided diagnosis (CAD) technology. The mo...