aceEvidence-backed problem
An ‘AI tax’ is driving up the price of gaming computers and other electronics
Massive demand from the data centres that power artificial intelligence is increasing the cost of digital memory for consumer electronics
All stories
877 published stories · page 20 of 59
Both readings
Establishing diagnostic thresholds for adult ADHD screening in taxi drivers: validation of the CAARS-S via Item Response Theory and Machine Learning
Background Adult Attention-Deficit/Hyperactivity Disorder (ADHD) is under-recognized in professional drivers, yet it poses significant safety risks. The Conners' Adult ADHD Rating Scale Short Version (CAARS-S:SV) lacks empirically validated cutoff scores for occupational screening in Iran. This study aimed to assess the psychometric properties of the Persian CAARS-S:SV in taxi drivers and to determine optimal ADHD diagnostic thresholds using both traditional and machine-learning methods. Methods A sample of 298…
Evidence-backed gain
Coupling machine learning with a biophysical model for maturity date prediction of apple fruit across China's apple planting regions
Background Accurate prediction of apple fruit maturity date is essential for optimizing harvest timing, fruit quality and market value under climate change. However, process-based crop models often show limited performance when extrapolated across large spatial scales, whereas machine learning models lack physiological interpretability. To address these limitations, this study has developed a hybrid framework integrating the process-based STICS model with machine learning approaches across China's apple planting…
Both readings
Exploratory machine learning-based early post-treatment assessment of willingness to reuse rubber dam isolation after microscopic root canal treatment
ObjectiveTo explore factors associated with willingness to reuse rubber dam isolation after microscopic root canal treatment and develop an exploratory machine learning-based early post-treatment assessment model.MethodsThis retrospective cross-sectional study included 306 patients who underwent microscopic root canal treatment with rubber dam isolation from May 2025 to November 2025. The outcome was the willingness to reuse rubber dam isolation at the 1-week follow-up. Forty-seven newly enrolled patients were r…
Both readings
From machine learning to deep learning in attention deficit hyperactivity disorder diagnosis: A bibliometric analysis of global trends (2011-2024)
Background The diagnosis of attention deficit hyperactivity disorder (ADHD) has traditionally relied on subjective clinical interviews. Recent years have witnessed a paradigm shift toward objective, data-driven diagnostics powered by artificial intelligence (AI). Objective This study provides a comprehensive bibliometric review of AI and machine learning (ML) applications in ADHD prediction to map the field's evolution, current trends, and future directions. Methods A structured search of the Scopus database ret…
Evidence-backed gain
Large Language Model-Based Localization of Premature Ventricular Contraction Origins: A Retrospective Diagnostic Accuracy Study
Background Accurate localization of premature ventricular contraction (PVC) origin from 12-lead electrocardiography (ECG) is important for procedural planning in catheter ablation. Although convolutional neural network (CNN)-based models have shown promising diagnostic performance, they require task-specific training and remain limited in interpretability. We evaluated whether large language model (LLM)-based ECG image interpretation could perform binary left-versus-right PVC origin localization from 12-lead ECG…
Evidence-backed gain
Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study
Objective To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial intelligence(AI)-derived coronary computed tomography angiography (CCTA) parameters combined with clinical indicators. Methods This retrospective study enrolled 114 patients with T2DM and non-obstructive coronary artery disease (1%-49% stenosis) who underwent CCTA at our hospital between September 2019 and September 2024. After follow-up of 1-5 years, patients were…
Performance of federated learning models in health services research: A systematic review and meta-analysis
Purpose This study aimed to assess the performance of federated learning (FL) models and compare their performance with local and centralized models. Methods We conducted a systematic search of Ovid MEDLINE and PubMed from inception to June 10, 2025, to identify studies using patient data to train or validate FL algorithms and reporting at least one model performance outcome. Two reviewers independently screened articles and extracted data on study characteristics, FL frameworks and model training methodologies,…
Artificial intelligence-based photographic detection of pink esthetic score attributes using a hybrid deep learning segmentation pipeline: a method development study
This study aimed to develop and internally validate a novel anatomy-driven artificial intelligence (AI) system for automated postoperative Pink Esthetic Score (PES) evaluation from intraoral photographs. Unlike most existing AI approaches, which rely on end-to-end prediction, the proposed pipeline derives PES attributes from anatomically grounded measurements. A hybrid analytical pipeline integrating instance segmentation and rule-based measurement was developed. Tooth crown segmentation was performed using Mask…
Integrating network toxicology, machine learning, and single-cell sequencing systems to analyze autophagy core genes in lung adenocarcinoma
The heterogeneity and complex tumor microenvironment of lung adenocarcinoma lead to poor prognosis. Autophagy, as a key cellular process, interacts with tumor immune infiltration and jointly affects the progression of lung adenocarcinoma, but its core regulatory genes and mechanisms are still unclear.This study integrated three lung adenocarcinoma transcriptome datasets from the GEO database and performed cross-analysis with the human autophagy gene set to screen for differentially expressed autophagy-related ge…
Delhi HC protects Yuvraj Singh's personality rights, says AI-generated deepfakes, unauthorised commercial use tarnish reputation, violate law
The Delhi High Court has protected Yuvraj Singh's personality rights. AI-generated deepfakes and unauthorised exploitation damage his reputation and commercial value. The court issued an interim injunction against creating and publishing such content. This order reinforces celebrity rights in the age of artificial intelligence. Violators of these rights will be dealt with severely.
Smart elections or rigged algorithms: the rise of artificial intelligence in electoral governance in Southeast Asia
Introduction Introducing Artificial Intelligence AI into electoral-management infrastructure has radically transformed the administrative practice in Southeast Asian democracies through streamlining voter registration, consolidating identification, and making the real-time observation of the electoral events possible. Although the benefits of AI are undoubtedly tangible in terms of efficiency, transparency, and accessibility, its appearance in contexts where such regulatory sanitation is antithetical presents sh…
Local Recurrence Prediction After Carbon-ion Radiotherapy for Early-stage Non-small Cell Lung Cancer Using Machine Learning
Background/aim Predicting local recurrence remains challenging in carbon-ion radiotherapy (CIRT) for non-small cell lung cancer (NSCLC). In this study, we aimed to develop and validate a machine learning model to predict local recurrence after CIRT for early-stage peripheral NSCLC. Patients and methods We retrospectively analyzed patients treated with CIRT at our institution between 2010 and 2020. An Extreme Gradient Boosting classifier using clinical parameters was developed to predict local recurrence within 2…
Was Jacqueline Fernandez's Viral 'Wardrobe Malfunction' Clip AI-Generated? Singer Sonu Thukral Files Police Complaint
Singer Sonu Thukral lodges a police complaint after an AI-edited viral clip claiming Jacqueline Fernandez suffered a wardrobe malfunction in the Jugni music video spreads online.
From bones to bytes: anticipating and addressing the governance challenges of human digital remains and posthumous digital human twins
Abstract During the nineteenth century, advances in medical research led to grave robbing and an illicit market in human biological remains (HBR). The historical episode of grave robbing illustrates how science can upend social norms. A similar scenario could soon emerge, but this time it will not be with people's biological remains, but with people's digital remains. Artificial intelligence and extended reality now create digital representations from avatars to human digital twins. In addition to the sophistica…
