± 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 27 of 59

Evidence-backed gain

Opportunities for Artificial Intelligence in Operational Medicine: Lessons from the United States Military

Conducted in challenging environments such as disaster or conflict areas, operational medicine presents unique challenges for the delivery of efficient and quality healthcare. It exposes first responders and medical personnel to many unexpected health risks and dangerous situations. To tackle these issues, artificial intelligence (AI) has been progressively incorporated into operational medicine, both on the front lines and also more recently in support roles. The ability of AI to rapidly analyze high-dimensiona…

Bioengineering · Health

Opportunities for Artificial Intelligence in Operational Medicine: Lessons from the United States Military
A foundation model for the Earth system
Evidence-backed gain

A foundation model for the Earth system

Reliable forecasting of the Earth system is essential for mitigating natural disasters and supporting human progress. Traditional numerical models, although powerful, are extremely computationally expensive1. Recent advances in artificial intelligence (AI) have shown promise in improving both predictive performance and efficiency2,3, yet their potential remains underexplored in many Earth system domains. Here we introduce Aurora, a large-scale foundation model trained on more than one million hours of diverse ge…

Climate
Integration of smart sensors and IOT in precision agriculture: trends, challenges and future prospectives
Both readings

Integration of smart sensors and IOT in precision agriculture: trends, challenges and future prospectives

Traditional farming methods, effective for generations, struggle to meet rising global food demands due to limitations in productivity, efficiency, and sustainability amid climate change and resource scarcity. Precision agriculture presents a viable solution by optimizing resource use, enhancing efficiency, and fostering sustainable practices through data-driven decision-making supported by advanced sensors and Internet of Things (IoT) technologies. This review examines various smart sensors used in precision ag…

Business
Large Language Models in Medicine: Applications, Challenges, and Future Directions
Both readings

Large Language Models in Medicine: Applications, Challenges, and Future Directions

In recent years, large language models (LLMs) represented by GPT-4 have developed rapidly and performed well in various natural language processing tasks, showing great potential and transformative impact. The medical field, due to its vast data information as well as complex diagnostic and treatment processes, is undoubtedly one of the most promising areas for the application of LLMs. At present, LLMs has been gradually implemented in clinical practice, medical research, and medical education. However, in pract…

Health
Evidence of a social evaluation penalty for using AI
Evidence-backed problem

Evidence of a social evaluation penalty for using AI

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further,…

Labor
Gender differences in artificial intelligence: the role of artificial intelligence anxiety
Evidence-backed problem

Gender differences in artificial intelligence: the role of artificial intelligence anxiety

Introduction: Artificial intelligence (AI) is having a significant impact on people's lives. Despite the benefits associated with this technological advancement, there may be gender-related inequalities in accessing and using AI systems. The present study aimed to test gender differences in factors likely to influence AI adoption, in particular, the moderating role of gender in the relationship between AI anxiety and positive attitudes toward AI. Method: Participants were 335 adults (52.2% women; mean age = 29.9…

Lifestyle
The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality
Both readings

The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality

The expanding domain of digital mental health is transitioning beyond traditional telehealth to incorporate smartphone apps, virtual reality, and generative artificial intelligence, including large language models. While industry setbacks and methodological critiques have highlighted gaps in evidence and challenges in scaling these technologies, emerging solutions rooted in co-design, rigorous evaluation, and implementation science offer promising pathways forward. This paper underscores the dual necessity of ad…

Health

A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation

Integrating large language models (LLMs) into healthcare can enhance workflow efficiency and patient care by automating tasks such as summarising consultations. However, the fidelity between LLM outputs and ground truth information is vital to prevent miscommunication that could lead to compromise in patient safety. We propose a framework comprising (1) an error taxonomy for classifying LLM outputs, (2) an experimental structure for iterative comparisons in our LLM document generation pipeline, (3) a clinical sa…

Health
A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation

Applications of AI-Based Models for Online Fraud Detection and Analysis

Abstract Background Fraud is a prevalent offence that extends beyond financial loss, impacting victims emotionally, psychologically, and physically. Advances in online communication technologies continue to create new opportunities for fraud, and fraudsters increasingly using these channels for deception. With the progression of technologies like Generative Artificial Intelligence (GenAI), there is a growing concern that fraud will increase in scale using these advanced methods, with offenders employing deep-fak…

Crime
Applications of AI-Based Models for Online Fraud Detection and Analysis

AI-Driven Wearable Bioelectronics in Digital Healthcare

The integration of artificial intelligence (AI) with wearable bioelectronics is revolutionizing digital healthcare by enabling proactive, personalized, and data-driven medical solutions. These advanced devices, equipped with multimodal sensors and AI-powered analytics, facilitate real-time monitoring of physiological and biochemical parameters-such as cardiac activity, glucose levels, and biomarkers-allowing for early disease detection, chronic condition management, and precision therapeutics. By shifting health…

Health
AI-Driven Wearable Bioelectronics in Digital Healthcare

When Is a Decision Automated? A Taxonomy for a Fundamental Rights Analysis

Abstract This Article addresses the pressing issues surrounding the use of automated systems in public decision-making, specifically focusing on migration, asylum, and mobility. Drawing on empirical data, this Article examines the potential and limitations of the General Data Protection Regulation and the Artificial Intelligence Act in effectively addressing the challenges posed by automated decision-making (ADM). The Article argues that the current legal definitions and categorizations of ADM fail to capture th…

Policy
When Is a Decision Automated? A Taxonomy for a Fundamental Rights Analysis

Performance of artificial intelligence in the collection of patient history in general practice

Automating administrative tasks, such as compiling a patient's medical history, could help general practitioners in their daily work. AI performance has improved in recent decades, but skepticism among professionals limits its use in medical practice, due to fears of gaps and biases. This study attempts to evaluate the effectiveness of AI in recording patient histories compared to general practitioners. Cross-sectional study. SITE: Online study in France. French general practitioners recruited online. We compare…

Health
Performance of artificial intelligence in the collection of patient history in general practice

Harnessing data science and artificial intelligence to advance implementation research and practice

Implementation science aims to bridge the gap between research evidence and routine health care practice by understanding and optimizing the integration of evidence-based interventions. In this paper, we identify seven persistent challenges limiting implementation progress, including (1) overwhelming volume of implementation materials (e.g., reports, interviews, surveys); (2) contextual variability; (3) complex interactions between contextual factors, interventions, and outcomes; (4) interest holder engagement c…

Science
Harnessing data science and artificial intelligence to advance implementation research and practice