Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
Between 2010 and 2020, 124 patients with early-stage peripheral non-small cell lung cancer treated with carbon-ion radiotherapy at a single institution were analyzed retrospectively to develop a machine learning predictor of local recurrence within 24 months. An Extreme Gradient Boosting classifier trained on clinical parameters with nested threefold cross-validation achieved ROC-AUC 0.622 and PR-AUC 0.145, and separated patients into low-risk and high-risk groups.
Researchers tested Inflammacheck, a point-of-care device that measures hydrogen peroxide in exhaled breath condensate plus physiological signals, combined with machine learning, in 34 participants from a UK lung health check programme where 83% of cancers were stage I-II. Multivariate analyses separated cancer and control groups, and a voting ensemble achieved 85.7% accuracy and 0.90 ROC-AUC on held-out data.
By August 2026, researchers had trained machine learning models on ADNI data to predict tau PET positivity from more accessible MRI and amyloid PET features, then tested them on OASIS-3 and SCAN cohorts. Logistic regression reached AUCs of 0.92 in both internal and external validation, with combined external accuracy of 85%.
On July 28, 2026, Scientific Reports published a framework for adaptive level modification that continuously infers player skill and restructures game content in real time. The system combines reinforcement learning agents and human data to classify skill, then uses a two-stage large language model pipeline to rewrite level chunks, with a physics-constrained verifier to preserve playability.
By July 2026, researchers reported a series of studies showing that when products were described as designed by AI, consumers rated them as less sustainable than when the same products were described as designed by humans, despite AI's efficiency potential.
A peer-reviewed study of 19 G20 countries from 2005 to 2023 used Generalized Method of Moments models to estimate how AI-related innovation relates to economic growth. The linear specification found a positive and significant effect, while the quadratic specification found a negative quadratic term indicating a concave pattern.
By July 2026, a peer-reviewed paper examined how proliferation of AI deepfake technologies allows unauthorized use of a person's likeness, including manipulation of images, voices and behaviours and dissemination without consent, affecting celebrities, politicians and private individuals on social media.
By June 2026, researchers documented a cybercrime pattern in Cirebon where perpetrators obtained children's photographs from social media or other digital platforms and manipulated them using Artificial Intelligence-based applications to produce indecent content.
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