Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
In a peer-reviewed study published June 25 2024, researchers surveyed 87 SMEs in France about their use of generative AI tools during the COVID-19 pandemic, geopolitical crises, and economic slowdown. Using a pre-tested survey and WarpPLS 7.0 modelling, they tested how generative AI and entrepreneurial orientation relate to entrepreneurial resilience under market turbulence.
In February 2024 the Council and European Parliament agreed on the AI Act, a risk-based regulation intended to ensure ethical and responsible AI use across the EU single market. The article examines the governance system in the April 2024 version of the text, noting the creation of a European Artificial Intelligence Office and planned Board, advisory forum, scientific panel, and national competent authorities.
In mid-2024, researchers reported results from a large-scale survey and follow-up interviews of innovation managers in the USA to assess how AI is actually used in innovation. They found adoption is high and widespread, with AI applied in more than half of surveyed firms' innovation projects and concentrated in the development stage rather than idea or commercialization stages.
On March 4, 2026, a peer-reviewed study in Frontiers in Artificial Intelligence reported results from 280 university students on an ESG-informed framework for Sustainable AI-Metaverse Adoption. Using SEM-PLS, the authors found environmental and social factors were stronger predictors of adoption than governance factors, and that sustainable adoption was linked to higher digital pedagogical innovation and enhanced student learning outcomes.
Researchers used a Causal Forest causal machine learning model on a retrospective cohort of gastric cancer patients treated between 2007 and 2017 to estimate who benefits from adjuvant chemotherapy. The model identified lymph node ratio as the most dominant predictor of benefit, with a significant interaction at a 0.25 threshold in a propensity-matched Stage II-III cohort.
This peer-reviewed educational perspective from August 2026 examined how organ-at-risk contouring is taught in an Australian undergraduate radiation therapy program as AI auto-contouring enters clinical workflows. The authors reviewed curriculum scope and technologies and examined students' preferred methods, confidence across OARs, and perceived factors affecting quality.
Researchers derived and tested the triglyceride-glucose frailty index in 2230 MIMIC-IV adults with KDIGO-defined AKI, examining associations with ICU, in-hospital, 28-day, 90-day and 365-day mortality, identifying two consensus phenotypes, and evaluating 12 prediction algorithms with SHAP and LIME interpretation and external validation in 1831 eICU patients.
On 2026-08-22, a peer-reviewed study reported testing how three different allometric reference datasets affect Sentinel-2-based aboveground biomass mapping in Pinus brutia. Using 112 field plots and CART as primary model with Random Forest as robustness check, authors mapped biomass over 13,687 ha and compared totals to forest management plan data.
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