Data‐driven optimization of sampling patterns for MR brain T1ρ mapping
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29445
Abstract: The goal of this study was to apply a fast data‐driven optimization algorithm, called bias‐accelerated subset selection, for MR brain T1ρ mapping to generate optimized sampling patterns (SPs) for compressed sensing reconstruction of brain 3D‐T1ρ… read more here.
Keywords: brain mapping; driven optimization; sampling patterns; brain ... See more keywords
Nurse Practitioner–Driven Optimization of Presurgical Testing
Sign Up to like & getrecommendations! Published in 2018 at "Journal of PeriAnesthesia Nursing"
DOI: 10.1016/j.jopan.2017.08.004
Abstract: &NA; Nurse practitioners play a pivotal role as members of the perioperative team. This article outlines the evolution of presurgical testing from the vantage of generic testing to one that is tailored to the patient's… read more here.
Keywords: nurse practitioner; driven optimization; optimization presurgical; presurgical testing ... See more keywords
Deep Learning-Driven Optimization of Antihypertensive Properties from Whey Protein Hydrolysates: A Multienzyme Approach.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of agricultural and food chemistry"
DOI: 10.1021/acs.jafc.4c10830
Abstract: This study utilized deep learning to optimize antihypertensive peptides from whey protein hydrolysate. Using the Large Language Models (LLMs), we identified an optimal multienzyme combination (MC5) with an ACE inhibition rate of 89.08% at a… read more here.
Keywords: deep learning; driven optimization; optimization antihypertensive; whey protein ... See more keywords
Pharmacokinetics-Driven Optimization of 4(3 H)-Pyrimidinones as Phosphodiesterase Type 5 Inhibitors Leading to TPN171, a Clinical Candidate for the Treatment of Pulmonary Arterial Hypertension.
Sign Up to like & getrecommendations! Published in 2019 at "Journal of medicinal chemistry"
DOI: 10.1021/acs.jmedchem.9b00123
Abstract: Phosphodiesterase type 5 (PDE5) inhibitors are first-line therapy for pulmonary arterial hypertension (PAH) and erectile dysfunction. As a continuing work to improve the terminal half-lives and oral bioavailabilities of our previously reported 4(3 H)-pyrimidones, a… read more here.
Keywords: phosphodiesterase type; driven optimization; pharmacokinetics driven; arterial hypertension ... See more keywords
Predictive Modeling and Data-Driven Optimization of CdFe2O4/p-Si Heterojunction Electrical Behavior
Sign Up to like & getrecommendations! Published in 2025 at "ACS Omega"
DOI: 10.1021/acsomega.5c06499
Abstract: This study investigates the electrical characteristics of a CdFe2O4/p-Si diode by integrating experimental techniques with machine learning (ML) approaches. The CdFe2O4 thin films were synthesized using the sol–gel spin coating method and deposited on a… read more here.
Keywords: driven optimization; optimization cdfe2o4; predictive modeling; data driven ... See more keywords
An observation-driven optimization method for continuous estimation of soil moisture over large heterogeneous areas
Sign Up to like & getrecommendations! Published in 2020 at "Remote Sensing Letters"
DOI: 10.1080/2150704x.2020.1731620
Abstract: ABSTRACT In most remote sensing-based soil moisture (SM) retrieval methods, in-situ SM measurements are commonly used for validation purposes. Few studies have investigated whether such measurements can be used for calibration. In this paper, an… read more here.
Keywords: optimization method; observation driven; method; driven optimization ... See more keywords
Threshold-driven optimization for reference-based auto-planning.
Sign Up to like & getrecommendations! Published in 2018 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aaa731
Abstract: We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used… read more here.
Keywords: auto planning; methodology; driven optimization; reference ... See more keywords
A Systematic Review of Wind Driven Optimization Algorithms and Their Variants
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3449998
Abstract: Wind Driven Optimization (WDO) Algorithm is a novel metaheuristic algorithm inspired by the continuous flow of air resulting from differences in air pressure until the air reaches a state of pressure balance. Owing to its… read more here.
Keywords: driven optimization; systematic review; wind driven; wdo ... See more keywords
AI-Driven Optimization of Smart Spaces: A WASPAS Decision Model to Intelligent Environment Design
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3572940
Abstract: Smart spaces are continually developing, needing cutting-edge ideas for better intelligent environment design to increase user experience, energy efficiency, and operational performance. This research presents a unique computational strategy that addresses the challenges of smart… read more here.
Keywords: intelligent environment; driven optimization; smart spaces; environment design ... See more keywords
Ecomap: Sustainability-Driven Optimization of Multi-Tenant DNN Execution on Edge Servers
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Computers"
DOI: 10.1109/tc.2025.3604487
Abstract: Edge computing systems struggle to efficiently manage multiple concurrent deep neural network (DNN) workloads while meeting strict latency requirements, minimizing power consumption, and maintaining environmental sustainability. This paper introduces Ecomap, a sustainability-driven framework that dynamically… read more here.
Keywords: sustainability driven; driven optimization; edge; ecomap sustainability ... See more keywords
Edge-Cloud Co-Evolutionary Algorithms for Distributed Data-Driven Optimization Problems.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3219452
Abstract: Surrogate-assisted evolutionary algorithms (EAs) have been proposed in recent years to solve data-driven optimization problems. Most existing surrogate-assisted EAs are for centralized optimization and do not take into account the challenges brought by the distribution… read more here.
Keywords: driven optimization; optimization; data driven; optimization problems ... See more keywords