Results 181 to 190 of about 152,215 (282)

In Silico Evaluation of Algorithm-Based Clinical Decision Support Systems Based on Care Pathway Simulation Models: Scoping Review. [PDF]

JMIR AI
Dorosan M, Chen YL, He Y, Zhuang Q, Lam SSW.   +4 more
europepmc   +1 more source

First genome sequence of a European Alternaria brassicae isolate and genes involved in early development of alternaria leaf spot on Brassica juncea

Pest Management Science, EarlyView.
This article reports the first genome sequence of a UK Alternaria brassicae isolate. Dual RNA‐sequencing profiling of A. brassicae‐infected Brassica juncea leaves identified differentially expressed genes involved in pathogenicity and host response pathways in moderately resistant Sej‐2 (2) and moderately susceptible Pusa Jaikisan cultivars.
Kevin M. King, Graham McLaughlin, Chinthani S. Karandeni Dewage, Zedi Gao, David J. Hughes, Jonathan S. West, Henrik U. Stotz   +6 more
wiley   +1 more source

Intranasal diamorphine population pharmacokinetics modeling and simulation in pediatric breakthrough pain

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 435-447, March 2025.
Abstract Intranasal diamorphine (IND), approved for managing breakthrough pain in the UK, has been identified as an acceptable alternative offering effective, expedient, and less traumatic analgesia for children. However, the current dose regimen in pediatric populations relies on clinical expertise while the pharmacokinetics properties are poorly ...
Lianjin Cai, Jingchen Zhai, Beihong Ji, Fengyang Han, Taoyu Niu, Luxuan Wang, Junmei Wang   +6 more
wiley   +1 more source

Generating Accurate Activity Patterns for Cattle Farm Management Using MCMC Simulation of Multiple-Sensor Data System. [PDF]

Sensors (Basel)
Hashimoto Y, Zin TT, Tin P, Kobayashi I, Hama H.   +4 more
europepmc   +1 more source

Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry   +4 more
wiley   +1 more source

Active guidance in ultrasound bladder scanning using reinforcement learning. [PDF]

Sci Rep
Hsu HL, Zahiri M, Li GY, Mukaddim RA, Lee H, Wilson MG, Grube J, Schmidt S, Ghoshal G, Raju B.   +9 more
europepmc   +1 more source

Impact of Packaging and Recycling Systems on Material Recirculation: A Stage‐Decomposition Model

Packaging Technology and Science, EarlyView.
A system‐level view emerges from decomposing recycling into four stages (participation, collection, sorting and process yield), diagnosing constraints and targeting interventions. Cumulative equivalent uses (CEUs) quantify long‐term retention, revealing marginal improvements at high baselines generate disproportionately larger gains than low‐baseline ...
Diogo Figueirinhas, Daniel Hellström, Henrik Pålsson, Yulia Vakulenko   +3 more
wiley   +1 more source

Cost-Utility Analysis of Renal Replacement Therapy Modalities in the Management of Severe Acute Kidney Injury in US Critically Ill Patients. [PDF]

Clinicoecon Outcomes Res
Martins R, Koyner J, Wald R, Harenski K, Echeverri J.   +4 more
europepmc   +1 more source

An objective Bayesian method for including parameter uncertainty in ensemble model output statistics

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Conventional model output statistics and ensemble model output statistics methods for calibrating ensemble forecasts lead to severe underestimation of the probabilities of ensemble extremes (in blue). This is because they ignore statistical parameter uncertainty.
Stephen Jewson, Leonardo Olivetti, Gabriele Messori, Paul J. Northrop, Trevor Sweeting   +4 more
wiley   +1 more source

HAO-AVP: An Entropy-Gini Reinforcement Learning Assisted Hierarchical Void Repair Protocol for Underwater Wireless Sensor Networks. [PDF]

Sensors (Basel)
Hao L, Ma C, Ao J.
europepmc   +1 more source