AIMC Topic: Monte Carlo Method

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Deep reconstruction model for dynamic PET images.

PloS one
Accurate and robust tomographic reconstruction from dynamic positron emission tomography (PET) acquired data is a difficult problem. Conventional methods, such as the maximum likelihood expectation maximization (MLEM) algorithm for reconstructing the...

Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This paper proposes a deep learning based ensemble regression estimator with asymptotic techniques, and offers a method that can decrease uncertainty for oscillometric blood pressure (BP) measurements using the bootstrap and...

A statistical framework for biomedical literature mining.

Statistics in medicine
In systems biology, it is of great interest to identify new genes that were not previously reported to be associated with biological pathways related to various functions and diseases. Identification of these new pathway-modulating genes does not onl...

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

Scientific reports
Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large ...

Using classification tree analysis to generate propensity score weights.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alte...

Princeton_TIGRESS 2.0: High refinement consistency and net gains through support vector machines and molecular dynamics in double-blind predictions during the CASP11 experiment.

Proteins
Protein structure refinement is the challenging problem of operating on any protein structure prediction to improve its accuracy with respect to the native structure in a blind fashion. Although many approaches have been developed and tested during t...

Feasibility of robotic stereotactic body radiotherapy of lung tumors with kilovoltage x-ray beams.

Medical physics
PURPOSE: Robotic Stereotactic body radiation therapy (SBRT) for lung tumors is treatment modality that, for cases of inoperable lung tumors, has shown excellent treatment outcomes. The typical photon energy when delivering this type of treatments is ...

Bayesian molecular design with a chemical language model.

Journal of computer-aided molecular design
The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techni...

Machine learning based compartment models with permeability for white matter microstructure imaging.

NeuroImage
Some microstructure parameters, such as permeability, remain elusive because mathematical models that express their relationship to the MR signal accurately are intractable. Here, we propose to use computational models learned from simulations to est...

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PloS one
Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scorin...