AIMC Topic: Markov Chains

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Robust path planning for flexible needle insertion using Markov decision processes.

International journal of computer assisted radiology and surgery
PURPOSE: Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path ...

Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques.

PloS one
The number of people diagnosed with dementia is expected to rise in the coming years. Given that there is currently no definite cure for dementia and the cost of care for this condition soars dramatically, slowing the decline and maintaining independ...

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

Artificial intelligence in medicine
OBJECTIVE: Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS ...

A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.

Medical image analysis
Heart motion tracking for radiation therapy treatment planning can result in effective motion management strategies to minimize radiation-induced cardiotoxicity. However, automatic heart motion tracking is challenging due to factors that include the ...

A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

BMC bioinformatics
BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes...

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.

PloS one
Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free B...

Approximate dynamic programming approaches for appointment scheduling with patient preferences.

Artificial intelligence in medicine
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the ...

Markovian encoding models in human splice site recognition using SVM.

Computational biology and chemistry
Splice site recognition is among the most significant and challenging tasks in bioinformatics due to its key role in gene annotation. Effective prediction of splice site requires nucleotide encoding methods that reveal the characteristics of DNA sequ...

Max-margin weight learning for medical knowledge network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of medical knowledge strongly affects the performance of intelligent diagnosis, and method of learning the weights of medical knowledge plays a substantial role in probabilistic graphical models (PGMs). The p...

A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning.

PLoS computational biology
Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and a...