All stories

1289 published stories · page 12 of 86

CrimeEvidence-backed problem

Radial wall strain for residual risk stratification after percutaneous coronary intervention

Background Percutaneous coronary intervention effectively treats flow-limiting stenoses; however, untreated non-target vessels with vulnerable plaques remain a major contributor to future adverse cardiovascular events. Plaque strain is a promising marker of plaque vulnerability but traditionally requires complex modelling and expensive intracoronary imaging. We developed a novel artificial intelligence algorithm for subpixel-level lumen delineation, enabling real-time automated assessment of radial wall strain (…

EuroIntervention

Evidence-backed problem

Image-Based Diagnosis of Oral Lesions: Performance of a Vision-Language Model versus Human Clinicians

Evidence-backed problem

Teaching AI-Informed Diagnostic Reasoning in Dental Education: A Conceptual Framework

Evidence-backed gain

Serum Protein Glycopatterns as Biomarkers for Machine Learning Diagnosis of Major Depressive Disorder

Evidence-backed problem

An application of random forest regression for predicting healthcare costs using administrative databases

Background Accurate healthcare cost predictions are essential for health economic decision-making. We propose a bottom-up approach that aggregates individual-level predictions to estimate expenditures for specific population segments without relying on a priori segmentation. Methods This retrospective population-based study used administrative healthcare data (2011-2023) from the Health Protection Agency of Bergamo (Italy). We traced 5-year healthcare resource utilization to predict individual's healthcare costs…

Evidence-backed problem

Applications of artificial intelligence in occupational noise assessment and noise‑related health outcomes: a scoping review

Occupational noise remains one of the most prevalent workplace hazards worldwide and is associated with a wide range of adverse health effects, particularly noise‑induced hearing loss (NIHL). Recently, artificial intelligence (AI) has been increasingly applied in occupational noise research; however, the scope and focus of these approaches have not been systematically mapped. This review aims to provide an overview of how AI has been used in occupational noise assessment and noise‑related health outcomes. Articl…

Evidence-backed gain

Development of an artificial intelligence model to estimate psychiatrist-assessed mental health-related presenteeism

Objectives This study aimed to contribute to the development of an AI-based system that supports worker health and productivity by enabling early detection of presenteeism. We tested whether an AI model could assess mental health-related presenteeism with accuracy comparable to that of psychiatrists and whether the frequency of application use was comparable between avatar-based and real-person interfaces. Methods This study aimed to design a multivariable prediction model among white-collar employees in a Japan…

Evidence-backed problem

Halt super-intelligent AI with non-proliferation treaty, Ed Davey to say

Ed Davey is to call for a global nuclear-style non-proliferation treaty to halt the development of super-intelligent AI when he makes his keynote speech at the Liberal Democrat conference, accusing Andy Burnham of relying on Donald Trump and “tech bros” to solve the problem. When he addresses the faithful on the final day of the gathering in Brighton, the party leader will call for a global pause on super-intelligent AI, comparing it to a nuclear arms race that could result in technology that could “destroy us a…

Health

Neural network analysis of the transmission dynamics of leptospirosis infection subject to vaccination and treatment interventions

The rapid spread of infectious diseases can lead to substantial casualties worldwide, with the greatest impact on economically disadvantaged and resource-deficient nations. The widespread transmission of infection disrupts social life and economic activities, amplifying their impact beyond the public health system. In this paper, we analyze the dynamics of leptospirosis disease considering treatment for humans and vaccination for the animal population along with environmental bacteria control. We analyzed the qu…

Health

[Tailoring care to the mind: The emerging role of artificial intelligence in precision psychiatry. Part II: Validating, regulating and integrating artificial intelligence into care]

Objectives Precision psychiatry seeks to tailor care to the clinical, biological, cognitive, behavioral, and contextual characteristics of each patient. Artificial intelligence may help achieve this goal by combining multimodal data, identifying complex patterns, following individual trajectories, and refining prognostic or therapeutic stratification. Yet strong statistical performance does not automatically translate into meaningful clinical benefit. This second part of Tailoring Care to the Mind: The Emerging…

Health

Multiscale model calibrated with a Bayesian algorithm predicts long-term outcomes of treatments for mitral valve regurgitation in animal models

In primary mitral valve regurgitation (MR), a failing valve induces volume overload (VO) of the left ventricle (LV), triggering neurohormonal responses and myocardial remodeling. Surgical valve repair is the most effective therapy for MR, improving symptoms and in some patients reversing cardiac hypertrophy. However, at least 20% of patients develop postoperative impairment of LV function with detrimental effects on long-term outcomes, with no known cause. Many MR patients receive pharmacological treatment to al…

Health

Smartphone AI-Enabled Lateral Flow Immunoassay Platform Using Advanced Quantum Dots for Intelligent Quantitative Diagnostics

Lateral flow immunoassays (LFIAs) are widely used in point-of-care diagnostics for their low cost and simplicity, but conventional formats rely on subjective visual readout and lack quantitative accuracy and sensitivity. Here, we present a smartphone-guided, artificial-intelligence-enhanced LFIA platform that unites a rationally engineered dual-modal nanoprobe with on-device machine learning, demonstrated for quantitative detection of Rift Valley fever virus (RVFV). The platform combines three synergistic princi…

Business

More Australians will be dying than being born in 40 years as major report predicts future of lower growth

There will be more Australians dying than being born in 40 years’ time, according to the government’s latest intergenerational report, which lays bare the fundamental challenges of managing an ageing population at a time of rapid change and lower economic growth. The country’s seventh IGR also outlines how Australia is at the cusp of a new and uncertain age of artificial intelligence that will shape the economy and society over the coming four decades. Jim Chalmers, in a speech at the Australian National Univers…

Business

AI slowdown calls justified but collapse of bubble may be more immediate threat | Heather Stewart

Warnings about powerful and uncontrolled AI have dominated the headlines this past week. But even amid the omens of apocalypse, it is still worth asking if the entire AI-industrial complex is sailing towards a financial iceberg. It will hardly be our most pressing concern if the bots are poised to take over the world, but a collapse of the AI bubble would have repercussions far beyond the US. AI bosses have united in recent days to warn us the immensely powerful product they have sunk billions into creating may…

Education

Predicting zero-dose vaccination status in 27 sub-Saharan African countries: a machine learning approach

To develop a machine learning (ML)-based predictive model for assessing the risk of zero-dose children using Demographic Health Survey data in sub-Saharan Africa. This study analysed pooled Demographic and Health Survey data from 27 countries in sub-Saharan Africa collected between 2016 and 2024. Data preprocessing included imputation, balancing of unequal classes and systematic feature selection. Seven ML models were trained and evaluated using performance metrics such as accuracy, recall and F1-score. Feature…