Results 201 to 210 of about 74,769 (254)

Applying machine learning to pharmacovigilance data: A proof‐of‐concept study

open access: yesBritish Journal of Clinical Pharmacology, Volume 92, Issue 10, Page 3503-3512, October 2026.
Aim Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance database (FNPV), this proof‐of‐concept study aimed to assess the feasibility of using a ML algorithm—eXtreme Gradient Boosting (XGBoost)—combined with SHapley Additive exPlanations (SHAP) analysis, to ...
Romain Barus   +6 more
wiley   +1 more source

AdipoRon Modulation of the Invasive Potential of Prostate Cancer Cells Is Dependent on Their EMT-Related Phenotype. [PDF]

open access: yesBiomedicines
Gabriel ALR   +6 more
europepmc   +1 more source

Model‐Enabled Knowledge Transfer Across Cell Lines, Culture Scales and Conditions

open access: yesBiotechnology and Bioengineering, Volume 123, Issue 10, Page 2613-2628, October 2026.
ABSTRACT Mechanistic models are central to quantitative understanding and optimization of Chinese hamster ovary (CHO) cell culture processes, but their utility is often restricted by parameter sets calibrated for specific cell lines, scales, or operating conditions.
Luxi Yu   +2 more
wiley   +1 more source

A Mechanism for Analyzing the Energy Consumption and Environmental Impact of LoRa Sensors Over Time

open access: yesInternational Journal of Communication Systems, Volume 39, Issue 15, October 2026.
An SPN‐based mechanism, validated against NS‐3 with MAPE below 0.3%, reveals how packet generation rate and spreading factor shape LoRa sensor lifetime, energy consumption, and operational CO2$$ {}_2 $$ emissions, supporting sustainable planning of large‐scale IoT deployments. ABSTRACT Long Range (LoRa) sensors are widely adopted in Internet of Things (
Vandirleya Barbosa   +5 more
wiley   +1 more source

NIRS Coupled With Machine Learning Algorithms for the Authentication and Quality Assessment of Indigenous Cattle and Buffalo Meat

open access: yeseFood, Volume 7, Issue 5, October 2026.
Portable NIRS combined with machine learning enabled rapid and accurate authentication of cattle and buffalo meat. Optimized models (XGBoost, CNN) achieved > 98% accuracy, while SHAP revealed key spectral regions. This dual approach offers a field‐ready, reagent‐free tool for fraud prevention and traceability. ABSTRACT Ensuring the authenticity of high‐
Dip Ghosh, Raad Al Deen, Md. Abul Hashem
wiley   +1 more source

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