± HEALTH Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and gener…+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…
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1046 published stories · page 36 of 70

Evidence-backed gain

Clinically Interpretable Deep Learning for Differentiating Vitiligo and Postinflammatory Hypopigmentation: Diagnostic Accuracy Study

Distinguishing vitiligo from postinflammatory hypopigmentation (PIH) is clinically challenging because both conditions may present with similar depigmented lesions. Although deep learning has shown strong potential for dermatologic image classification, limited interpretability remains a barrier to clinical adoption. This study aimed to develop an interpretable deep learning framework for accurate differentiation between vitiligo and PIH using a lightweight convolutional neural network and an ensemble of explain…

JMIR Medical Informatics · Health

Clinically Interpretable Deep Learning for Differentiating Vitiligo and Postinflammatory Hypopigmentation: Diagnostic Accuracy Study
Persona-Driven Data Augmentation for Disease Name Recognition Across Rare and General Disease Corpora: Comparative Evaluation Study
Evidence-backed gain

Persona-Driven Data Augmentation for Disease Name Recognition Across Rare and General Disease Corpora: Comparative Evaluation Study

Medical information extraction requires automatically identifying disease names and related terms in text. This task, known as named entity recognition (NER), relies on expert-annotated data that are costly to produce and often available only in limited quantities. Data augmentation (DA) aims to expand available training data; however, standard techniques such as synonym replacement and back-translation may introduce inappropriate substitutions or fail to preserve entity-label alignment, which is critical for se…

Health
The single-cell atlas of programmed cell death signature: A machine learning-based prognostic framework in breast cancer
Evidence-backed gain

The single-cell atlas of programmed cell death signature: A machine learning-based prognostic framework in breast cancer

Breast cancer remains a leading cause of cancer-related mortality in women, and current prognostic models are suboptimal. The transcriptomic role of programmed cell death (PCD) in breast cancer progression is not fully understood. Here, we integrated single-cell RNA sequencing data from breast tumors with nine bulk transcriptomic cohorts to systematically analyze 19 PCD modalities. Using a machine learning framework incorporating 14 algorithms, we constructed a prognostic signature, with a ridge regression-based…

Health
Germany Tightens Reins on AI Content: Google and Perplexity in Spotlight
Evidence-backed problem

Germany Tightens Reins on AI Content: Google and Perplexity in Spotlight

Germany's media regulator has ruled that Google's AI Overviews and Perplexity AI must comply with the country’s media laws. The decision arises after a court held Google accountable for inaccuracies in AI-produced content, declaring AI summaries as proprietary rather than third-party material.

Policy
Germany Tightens Grip on AI-Generated Content: Google and Perplexity Under Scrutiny
Evidence-backed problem

Germany Tightens Grip on AI-Generated Content: Google and Perplexity Under Scrutiny

Germany's media regulator has decided that AI-generated content from Google and Perplexity AI falls under national media laws. A German court ruled Google directly liable for misinformation from its AI Overview feature, intensifying scrutiny of the technology. AI-produced content will be treated as originating from the providers themselves.

Policy

EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements

The discovery and optimization of high-energy materials (HEMs) face challenges due to the computational expense and slow iteration of traditional methods. Neural network potentials (NNPs) have emerged as an efficient alternative to first-principles simulations. This study presents EMFF-2025, a general NNP model for C, H, N, and O-based HEMs, leveraging transfer learning with minimal data from DFT calculations. The model achieves DFT-level accuracy, predicting the structure, mechanical properties, and decompositi…

Science
EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements

Prognostic Significance of Cell-Free DNA Derived 5-Hydroxymethylcytosine Signatures in Newly Diagnosed Multiple Myeloma

While survival outcomes in multiple myeloma (MM) have improved with contemporary combination therapies, predicting disease trajectories for individual patients at diagnosis remains a significant challenge. We investigate the prognostic value of a noninvasive biomarker-cell-free DNA (cfDNA)‑derived 5-hydroxymethylcytosine (5hmC) signature-in newly diagnosed MM, aiming to improve risk stratification at diagnosis. In this prospective cohort study, 321 patients with newly diagnosed MM were enrolled between 2010 and…

Health
Prognostic Significance of Cell-Free DNA Derived 5-Hydroxymethylcytosine Signatures in Newly Diagnosed Multiple Myeloma

‘Customers prefer AI chatbots,’ says British Gas owner as 1,300 call centre jobs axed

The owner of British Gas has claimed that most households would rather speak with an AI chatbot than deal with the company’s staff as it prepares to cut 1,300 jobs from its call centres. Centrica, the supplier’s FTSE 100 owner, plans to cut 800 jobs as the company carries out a “targeted deployment of AI tools”, on top of the 500 cuts it confirmed last month. The plan to reduce the supplier’s customer service teams in Glasgow, Edinburgh, Cardiff, Leicester, Stockport and Leeds by 14% is expected to take place ov…

Labor
‘Customers prefer AI chatbots,’ says British Gas owner as 1,300 call centre jobs axed

Digital Transformation in Accounting: An Assessment of Automation and AI Integration

This study conducts a bibliometric analysis of the scientific literature on digital, automated, and AI-assisted accounting systems. The data include documents listed in the Web of Science and Scopus databases. The analysis identifies the main authors, countries/territories, sources, and thematic trends. The results reveal that the scientific output within this research field has increased since 2018, emphasising the integration of artificial intelligence (AI), robotic process automation, and blockchain technolog…

Science
Digital Transformation in Accounting: An Assessment of Automation and AI Integration

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups. Draft recommendation items were informed by a systematic review and stakeh…

Science
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Federated Learning in Smart Healthcare: A Comprehensive Review on Privacy, Security, and Predictive Analytics with IoT Integration

Federated learning (FL) is revolutionizing healthcare by enabling collaborative machine learning across institutions while preserving patient privacy and meeting regulatory standards. This review delves into FL's applications within smart health systems, particularly its integration with IoT devices, wearables, and remote monitoring, which empower real-time, decentralized data processing for predictive analytics and personalized care. It addresses key challenges, including security risks like adversarial attacks…

Health
Federated Learning in Smart Healthcare: A Comprehensive Review on Privacy, Security, and Predictive Analytics with IoT Integration

Generative AI in higher education: A global perspective of institutional adoption policies and guidelines

Integrating generative AI (GAI) into higher education is crucial for preparing a future generation of GAI-literate students. However, a comprehensive understanding of global institutional adoption policies remains absent, with most prior studies focusing on the Global North and lacking a theoretical lens. This study utilizes the Diffusion of Innovations Theory to examine GAI adoption strategies in higher education across 40 universities from six global regions. It explores the characteristics of GAI innovation,…

Education
Generative AI in higher education: A global perspective of institutional adoption policies and guidelines