AIMC Topic: Machine Learning

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Extract Features from Periocular Region to Identify the Age Using Machine Learning Algorithms.

Journal of medical systems
Latest studies done on huge data collected from aging features proved that the performance of facial image based age estimation is low and need to be improved. One of the significant biometric traits for human recognition or search is Human age. Age ...

Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

Journal for immunotherapy of cancer
BACKGROUND: Targeting epitopes derived from neo-antigens (or "neo-epitopes") represents a promising immunotherapy approach with limited off-target effects. However, most peptides predicted using MHC binding prediction algorithms do not induce a CD8 +...

See your mental state from your walk: Recognizing anxiety and depression through Kinect-recorded gait data.

PloS one
As the challenge of mental health problems such as anxiety and depression increasing today, more convenient, objective, real-time assessing techniques of mental state are in need. The Microsoft Kinect camera is a possible option for contactlessly cap...

Learning, planning, and control in a monolithic neural event inference architecture.

Neural networks : the official journal of the International Neural Network Society
We introduce REPRISE, a REtrospective and PRospective Inference SchEme, which learns temporal event-predictive models of dynamical systems. REPRISE infers the unobservable contextual event state and accompanying temporal predictive models that best e...

Testing the ability of unmanned aerial systems and machine learning to map weeds at subfield scales: a test with the weed Alopecurus myosuroides (Huds).

Pest management science
BACKGROUND: It is important to map agricultural weed populations to improve management and maintain future food security. Advances in data collection and statistical methodology have created new opportunities to aid in the mapping of weed populations...

How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.

Journal of diabetes science and technology
BACKGROUND: Self-monitoring blood glucose (SMBG) is facilitated by application available to analyze these data. They are mainly based on descriptive statistical analyses. In this study, we are proposing a method inspired by artificial intelligence al...

Learning-based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery.

Medical physics
PURPOSE: Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM. Manual segmentation during a framed SRS procedure is time consuming and su...

Evaluating and Enhancing the Generalization Performance of Machine Learning Models for Physical Activity Intensity Prediction From Raw Acceleration Data.

IEEE journal of biomedical and health informatics
PURPOSE: To evaluate and enhance the generalization performance of machine learning physical activity intensity prediction models developed with raw acceleration data on populations monitored by different activity monitors.

Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Nature biomedical engineering
Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time an...