Cost-Effectiveness Analysis of Different Prenatal Screening Strategies for the Prevention of Severe Thalassemia in Thailand. [PDF]
Malasai K +5 more
europepmc +1 more source
This study proposes a method to increase the value of solar power in balancing markets by managing prediction errors. The approach models prediction uncertainties and quantifies reserve requirements based on a probabilistic model. This enables the more reliable participation of photovoltaic plants in balancing markets across multiple sites, especially ...
Jindan Cui +3 more
wiley +1 more source
Enhancing Naloxone Distribution for Opioid Users in the USA: A Cost-Utility Analysis of Academic Detailing to Clinicians. [PDF]
Yip O, Bounthavong M.
europepmc +1 more source
GBDT-IL: Incremental Learning of Gradient Boosting Decision Trees to Detect Botnets in Internet of Things [PDF]
Ruidong Chen +5 more
openalex +1 more source
Supply chain risk in grain trading: Inventories as real options for shipping grain
Abstract Integrating trading and logistics is an important challenge in commodity trading. Trading and logistics are strategic decisions and are integral to most commodities including grain shipping by rail, in addition to other modes (barges, ocean shipping). There are substantial risks, such as the ordering and placement of rail cars.
William W. Wilson, Jesse Klebe
wiley +1 more source
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
Cost-effectiveness of olorofim in the treatment of invasive aspergillosis in patients with limited suitable alternative treatment options: a US payer perspective. [PDF]
Walsh TJ +7 more
europepmc +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Cost-Effectiveness Analysis of Aztreonam-Avibactam (ATM-AVI) Versus Colistin + Meropenem (COL + MER) for the Treatment of Infections Caused by Metallo-β-Lactamase (MBL)-Producing Enterobacterales in Italy. [PDF]
Falcone M +6 more
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source

