AIMC Topic: Algorithms

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Image Reconstruction is a New Frontier of Machine Learning.

IEEE transactions on medical imaging
Over past several years, machine learning, or more generally artificial intelligence, has generated overwhelming research interest and attracted unprecedented public attention. As tomographic imaging researchers, we share the excitement from our imag...

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

IEEE transactions on neural networks and learning systems
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control track...

Multisource Transfer Double DQN Based on Actor Learning.

IEEE transactions on neural networks and learning systems
Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential ...

Applications of Deep Learning and Reinforcement Learning to Biological Data.

IEEE transactions on neural networks and learning systems
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine ...

Development and Evaluation of an Automated Machine Learning Algorithm for In-Hospital Mortality Risk Adjustment Among Critical Care Patients.

Critical care medicine
OBJECTIVES: Risk adjustment algorithms for ICU mortality are necessary for measuring and improving ICU performance. Existing risk adjustment algorithms are not widely adopted. Key barriers to adoption include licensing and implementation costs as wel...

Expanding a radiology lexicon using contextual patterns in radiology reports.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Distributional semantics algorithms, which learn vector space representations of words and phrases from large corpora, identify related terms based on contextual usage patterns. We hypothesize that distributional semantics can speed up lex...

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Nucleosome positioning plays significant roles in proper genome packing and its accessibility to execute transcription regulation. Despite a multitude of nucleosome positioning resources available on line including experimental datasets o...

Context encoding enables machine learning-based quantitative photoacoustics.

Journal of biomedical optics
Real-time monitoring of functional tissue parameters, such as local blood oxygenation, based on optical imaging could provide groundbreaking advances in the diagnosis and interventional therapy of various diseases. Although photoacoustic (PA) imaging...