± HEALTH Colorectal Cancer (CRC) is a common cause of cancer death and prognostic factors are used to determine manage…+ HEALTH This multicenter study developed and validated an interpretable machine learning model integrating granular n…+ HEALTH Multiple stakeholders need to locate results of registered clinical trials but frequently struggle to find th…+ HEALTH Accurate preoperative glioma grading and molecular subtyping are important for treatment. The vascular microe…+ HEALTH Gastrointestinal endoscopy generates extensive high-resolution video data, posing significant challenges for…+ HEALTH Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and invasive encapsulat…+ POLICY Artificial intelligence (AI) has the potential to strengthen real-world evidence (RWE) for regulatory decisio…± HEALTH Echocardiography remains the cornerstone of cardiovascular imaging. However, traditional workflows including…
TruaceTracing the truth around AIFriday, August 28, 2026
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877 published stories · page 3 of 59

Evidence-backed gain

Tissue-Agnostic Cellular Morphometric Biomarkers for Risk-Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers

While precision oncology increasingly adopts tissue-agnostic paradigms, current strategies remain heavily reliant on molecular alterations, with limited relevance to early-stage cancers and precancerous lesion management. Here we present an unsupervised and interpretable artificial intelligence framework that defines tissue-agnostic cellular morphometric biomarkers (CMBs) capturing conserved tumor microenvironment (TME) architectures associated with cancer progression across gastrointestinal (GI) organs. Discove…

Advanced Science · Health

Tissue-Agnostic Cellular Morphometric Biomarkers for Risk-Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers
Forensic analysis of dominant versus non-dominant handwriting: Statistical and machine learning insights
Evidence-backed gain

Forensic analysis of dominant versus non-dominant handwriting: Statistical and machine learning insights

Systematic, paired quantitative evidence on how handwriting changes when the non-dominant hand is used remains limited in forensic document examination, despite its frequent relevance in cases involving disguise and authorship concealment. This study presents the first large-scale within-writer analysis examining general and individual handwriting characteristics using statistical testing and predictive modeling. Handwriting samples were collected from 94 right-handed participants, each of whom produced the same…

Crime
US building twice as much gas-fired capacity as China in AI boom, analysis finds
Evidence-backed problem

US building twice as much gas-fired capacity as China in AI boom, analysis finds

The US has surged ahead of China in the building of new gas-fired power generation, largely to feed a boom in artificial intelligence (AI) that is adding vast amounts of planet-heating emissions, a new analysis has found. For decades, China’s rapid economic growth has seen it outpace the US in the addition of new gas power generation but a recent “frenzy” in datacenter construction for AI has reversed this, said Global Energy Monitor (Gem) in its new report. The US is now building twice as much gas-fired capacit…

Climate

Stylometric comparisons of human versus AI-generated creative writing

This study employs stylometry to investigate whether the creative writing styles of humans and large language models (LLMs) such as GPT-3.5, GPT-4, and Llama 70b can be distinguished through quantitative analysis. A balanced dataset of short stories composed in response to predefined narrative prompts forms the basis of the analysis. Burrows’ Delta, a widely used metric in computational literary studies, is applied to measure stylistic similarity and difference across texts. By focusing on the distribution of th…

Media & Arts
Stylometric comparisons of human versus AI-generated creative writing

Generative AI Art and Creative Subjectivity: A Mixed-Methods Study Based on Grounded Theory and CRITIC

With the rapid application of Generative AI technologies in image generation, style transfer, and creative assistance, the process and logic of artistic creation are undergoing a profound transformation.However, research on how AI art platforms influence creators' subjectivity remains limited, and few studies have systematically examined users' real-world experiences.To bridge this gap, this study investigated three representative AI art platforms -Midjourney, Runway ML, and Stable Diffusion -using a mixed-metho…

Media & Arts
Generative AI Art and Creative Subjectivity: A Mixed-Methods Study Based on Grounded Theory and CRITIC

Enhanced classification and identification of bacterial and viral microorganisms by integration of MALDI-TOF mass spectrometry with artificial intelligence

The accurate and rapid identification of bacterial pathogens is essential in clinical setups and medical biodefense. Matrix-Assisted Laser Desorption Ionization Time-Of-Flight (MALDI-TOF) mass spectrometry has emerged as a powerful tool for fast and reliable microbial identification. This study assesses the performance of eight Machine Learning (ML) and two Deep Learning (DL) models trained using 5-fold cross validation in classifying microorganisms in a series of experiments based on MALDI-TOF mass spectra (n =…

Health
Enhanced classification and identification of bacterial and viral microorganisms by integration of MALDI-TOF mass spectrometry with artificial intelligence

Overcoming the opaque side of AI in healthcare: a lifecycle based approach

Introduction Transparency has emerged as a foundational condition for trustworthy Artificial Intelligence (AI) in healthcare. Despite its centrality, practical approaches to systematically operationalize transparency across the entire lifecycle of AI-enabled medical devices remain fragmented and insufficiently structured. This work addresses this gap by proposing a lifecycle-oriented operational approach to guide the consistent implementation and evaluation of transparency in AI-based medical technologies. Areas…

Health
Overcoming the opaque side of AI in healthcare: a lifecycle based approach

Pathogenic Genetic Variants, Comorbid Autism and Adaptive Developmental Quotient as Independent Predictors of Intellectual Disability in Children With Global Developmental Delay: An Interpretable Machine Learning Model With Calibrated Risk Estimation

Background Global developmental delay (GDD) frequently precedes intellectual disability (ID), but no validated multivariable prognostic tool exists to support individualised counselling during the initial diagnostic work-up. Existing risk indicators are typically considered in isolation, and their joint contribution within an interpretable predictive framework remains uncertain. Methods We retrospectively analysed 2453 children diagnosed with GDD between January 2014 and December 2023 at a provincial tertiary ch…

Health
Pathogenic Genetic Variants, Comorbid Autism and Adaptive Developmental Quotient as Independent Predictors of Intellectual Disability in Children With Global Developmental Delay: An Interpretable Machine Learning Model With Calibrated Risk Estimation

From accuracy to service: deciding what artificial intelligence outputs may do in veterinary diagnostic laboratories

Artificial intelligence (AI) tools are entering veterinary diagnostic laboratory service, but reported model accuracy does not determine what the laboratory staff should allow an output to do. This Commentary defines service entry as the point at which an AI output is allowed to influence case triage, interpretation, a draft report, or result release. Before that point, the laboratory staff should first decide whether the submitted specimen can support the question being asked. They should then document 7 decisi…

Health
From accuracy to service: deciding what artificial intelligence outputs may do in veterinary diagnostic laboratories

Dynamic liquid with shape-shifting induced photocurrent variation in a CuBi<sub>2</sub>O<sub>4</sub> film for antimicrobial biocide recognition

Antimicrobial biocides play a crucial role in infection control. Although traditional detection methods are accurate, they are cumbersome to operate, require trained personnel, and provide only basic recognition without intelligent analysis. Therefore, given the critical role of biocide type and concentration in effective disinfection, there is an urgent need for portable and intelligent monitoring technologies. Here, we present an optical sensor based on an ITO/CuBi 2 O 4 /LaNiO 3 heterojunction. The device fea…

Health
Dynamic liquid with shape-shifting induced photocurrent variation in a CuBi<sub>2</sub>O<sub>4</sub> film for antimicrobial biocide recognition