AIMC Topic: Machine Learning

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PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

Behavior research methods
Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional u...

Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

Journal of digital imaging
Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can improve diagnostic accuracy and save lives. CNNs have been successfully used in both skin lesion segme...

Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.

Neurosurgery
BACKGROUND: Machine learning (ML) is a domain of artificial intelligence that allows computer algorithms to learn from experience without being explicitly programmed.

Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence.

Investigative ophthalmology & visual science
PURPOSE: While millions of individuals show early age-related macular degeneration (AMD) signs, yet have excellent vision, the risk of progression to advanced AMD with legal blindness is highly variable. We suggest means of artificial intelligence to...

SpiroConfidence: Determining the Validity of Smartphone Based Spirometry Using Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prior work has shown that smartphone spirometry can effectively measure lung function using the phone's built-in microphone and could one day play a critical role in making spirometry more usable, accessible, and cost-effective. Although traditional ...

Improving Young Stroke Prediction by Learning with Active Data Augmenter in a Large-Scale Electronic Medical Claims Database.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electronic medical claims (EMC) database has been successfully used for predicting occurrences of stroke and a variety of other diseases. However, inadequate predictive performances have been observed in cases of rare occurrences due to both insuffic...

Medhere: A Smartwatch-based Medication Adherence Monitoring System using Machine Learning and Distributed Computing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Poor medication adherence threatens an individual's health and is responsible for substantial medical costs in the United States annually. In order to improve medication adherence rates and provide timely reminders, we developed a smartwatch applicat...

Early Identification of Patentable Medical Innovations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
There is considerable interest in developing methods for early detection of medical advances which are likely to lead to effective treatments. Because the number of potentially significant discoveries published each year is very large, practically-us...

Evaluating ICU Clinical Severity Scoring Systems and Machine Learning Applications: APACHE IV/IVa Case Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Clinical scoring systems have been developed for many specific applications, yet they remain underutilized for common reasons such as model inaccuracy and difficulty of use. For intensive care units specifically, the Acute Physiology and Chronic Heal...

Interpretable Machine Learning Techniques for Causal Inference Using Balancing Scores as Meta-features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Estimating individual causal effect is important for decision making in many fields especially for medical interventions. We propose an interpretable and accurate algorithm for estimating causal effects from observational data. The proposed scheme is...