Results 191 to 200 of about 256,437 (324)

Accelerating virtual patient generation with a Bayesian optimization and machine learning surrogate model

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 486-494, March 2025.
Abstract The pharmaceutical industry has increasingly adopted model‐informed drug discovery and development (MID3) to enhance productivity in drug discovery and development. Quantitative systems pharmacology (QSP), which integrates drug action mechanisms and disease complexities to predict clinical endpoints and biomarkers is central to MID3.
Hiroaki Iwata, Ryuta Saito
wiley   +1 more source

A Markov random field model with cumulative logistic functions for spatially dependent ordinal data. [PDF]

J Appl Stat
Ip RHL, Wu KYK.
europepmc   +1 more source

Bivariate postprocessing of wind vectors

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner, David Jobst, Annette Möller, Claudia Czado   +3 more
wiley   +1 more source

Automated attendance system using markov random field algorithm

, 2014
ABHILASH MARADWAR, Nikita Suryawanshi, Tushar Panpaliya, SURAJ SONGIRE   +3 more
openalex   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source

Segmentation of MS lesions using entropy-based EM algorithm and Markov random fields

, 2011
Ahmad Bijar, Mahdi Mohamad Khanloo, Antonio Peñalver, Rasoul Khayati   +3 more
openalex   +2 more sources

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI. [PDF]

Front Neuroinform, 2017
Castillo-Barnes D, Peis I, Martínez-Murcia FJ, Segovia F, Illán IA, Górriz JM, Ramírez J, Salas-Gonzalez D.   +7 more
europepmc   +1 more source

Incorporating environmental DNA metabarcoding for improved benthic biodiversity and habitat mapping

Remote Sensing in Ecology and Conservation, EarlyView.
Seafloor imagery is commonly used to collect information about the distribution of benthic organisms in order to generate habitat and biodiversity maps. Recent advances in genomics (e.g., environmental DNA; eDNA) show potential to complement video surveys for habitat mapping, but there have been few examples testing this.
Rylan J. Command, Shreya Nemani, Benjamin Misiuk, Mehrdad Hajibabaei, Nicole Fahner, Emily Porter, Greg Singer, Beverly McClenaghan, Katleen Robert   +8 more
wiley   +1 more source

Markov random fields factorization with context-specific independences [PDF]

, 2013
Alejandro Edera, Facundo Bromberg, Federico Schlüter   +2 more
openalex   +1 more source

Structure and functional genes associated with carbon, nitrogen, phosphorus, and sulfur cycling processes in periphyton: A comparison between natural and artificial rivers

River, EarlyView.
Network analysis of functional genes among prokaryotes, and eukaryotes in natural and artificial rivers. Abstract Periphyton in aquatic ecosystems plays vital roles in the elemental cycle process and is vulnerable to anthropogenic interference. However, few studies have explored the elemental cycles of carbon (C), nitrogen (N), phosphorus (P), and ...
Yulu Tian, Jiezhang Mo, Jiaxin Liu, Chenghao Li, Jiahua Guo   +4 more
wiley   +1 more source