AIMC Topic: Machine Learning

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Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.

Methods (San Diego, Calif.)
Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last decade due to numerous technological breakthroughs. Imaging is now playing a critical role on deployment of the clinical workflow, both for treatment plan...

Fast Deep Stacked Networks based on Extreme Learning Machine applied to regression problems.

Neural networks : the official journal of the International Neural Network Society
Deep learning techniques are commonly used to process large amounts of data, and good results are obtained in many applications. Those methods, however, can lead to long training times. An alternative to simultaneously tune all parameters of a large ...

Predictors of emergency department opioid administration and prescribing: A machine learning approach.

The American journal of emergency medicine
INTRODUCTION: The opioid epidemic has altered normative clinical perceptions on addressing both acute and chronic pain, particularly within the Emergency Department (ED) setting, where providers are now confronted with balancing pain management and p...

Classification of Microarray Gene Expression Data Using an Infiltration Tactics Optimization (ITO) Algorithm.

Genes
A number of different feature selection and classification techniques have been proposed in literature including parameter-free and parameter-based algorithms. The former are quick but may result in local maxima while the latter use dataset-specific ...

Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study.

International journal of environmental research and public health
Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pe...

Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

The Annals of thoracic surgery
BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).

Opportunities and challenges in the collection and analysis of digital phenotyping data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
The broad adoption and use of smartphones has led to fundamentally new opportunities for capturing social, behavioral, and cognitive phenotypes in free-living settings, outside of research laboratories and clinics. Predicated on the use of existing p...

Cuffless Blood Pressure Monitoring: Promises and Challenges.

Clinical journal of the American Society of Nephrology : CJASN
Current BP measurements are on the basis of traditional BP cuff approaches. Ambulatory BP monitoring, at 15- to 30-minute intervals usually over 24 hours, provides sufficiently continuous readings that are superior to the office-based snapshot, but t...