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1289 published stories · page 16 of 86

Retrospective comparison of three commercial artificial intelligence algorithms for detection of intracranial hemorrhage (ICH) in the emergency radiology department
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Retrospective comparison of three commercial artificial intelligence algorithms for detection of intracranial hemorrhage (ICH) in the emergency radiology department

BackgroundSeveral commercial artificial intelligence (Al) algorithms are available for detecting intracranial hemorrhage (ICH), but independent clinical validation remains limited.PurposeTo compare three commercially available Al algorithms for ICH detection on non- contrast head computed tomography (NCHCT).Material and MethodsIn this retrospective study, 4027 consecutive NCHCT examinations from a large emergency hospital in southwest Sweden were analyzed. Three Al algorithms were applied, with one vendor disclo…

Acta Radiologica
Arch Manning apologizes for ‘insensitive’ joke about AI video of ESPN’s Holly Rowe
Evidence-backed problem

Arch Manning apologizes for ‘insensitive’ joke about AI video of ESPN’s Holly Rowe

Texas’s star quarterback, Arch Manning, has apologized after joking about an AI-generated video that depicted Longhorns coach Steve Sarkisian slapping ESPN college football reporter Holly Rowe after last Saturday’s game. Manning had been asked at a press conference on Monday about the social media reaction to the Longhorns’ 24-23 upset win over No 1 Ohio State. Rowe had attempted to ask Sarkisian a question for the standard postgame interview, but the coach interrupted her and yelled a pair of Texas slogans befo…

As the politicians play catchup the tech bros agree: we may only have a decade left | John Crace
Evidence-backed problem

As the politicians play catchup the tech bros agree: we may only have a decade left | John Crace

We can all sleep easy. In a post on his Truth Social account, Donald Trump has declared that fears over artificial intelligence were all a hoax dreamed up by conspiracy theorists. Obviously that includes the top bods at Anthropic and its competitors, who all called for a coordinated global slowdown while the industry works out how to mitigate the risks. Still, good to know the tech bros are just fantasists and space cadets at heart. All that was needed to keep humanity safe and well, The Donald insisted, was a p…

Artificial intelligence ‐ driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals
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Artificial intelligence ‐ driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals

Abstract This study presents a comprehensive literature review using a systematic approach to explore the role of artificial intelligence (AI) in promoting sustainable development in line with the United Nations Sustainable Development Goals (SDGs). The systematic review approach was applied to collect and analyze topics, and the literature search was conducted in two stages, encompassing 57 articles that met the research requirements. Our analysis reveals that AI's contribution to sustainability is concentrated…

Leveraging generative artificial intelligence for simulation-based physics experiments: A new approach to virtual learning about the real world
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Leveraging generative artificial intelligence for simulation-based physics experiments: A new approach to virtual learning about the real world

This study investigates the impact of a novel application of generative artificial intelligence (AI) in physics instruction: engaging students in prompting, refining, and validating AI-constructed simulations of physical phenomena. In a second-semester physics course for life science majors, we conducted a comparative study of three instructional approaches in a laboratory focused on electric p...

Health

Artificial Intelligence at the Boundary of Spiritual Experience and Psychopathology: A Scoping Review of Evidence from Türkiye, the USA, the UK, Poland, South Korea, and Israel

The rapid integration of artificial intelligence (AI) into everyday life has created new intersections among digital technology, spirituality, mystical experience, and psychopathology. This scoping review aimed to map evidence on how AI mediates, reinforces, detects, predicts, or interprets religious and spiritual experiences at the boundary with psychosis and dissociation. PubMed, Web of Science, Embase, the Cochrane Library, and Scopus were searched through June 30, 2026, with supplementary reference-list scre…

Artificial Intelligence at the Boundary of Spiritual Experience and Psychopathology: A Scoping Review of Evidence from Türkiye, the USA, the UK, Poland, South Korea, and Israel
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Radiomics and dosiomics in radionecrosis prediction in brain metastasis treated with Stereotactic Radiation Therapy: a machine learning approach

Introduction Stereotactic Radiotherapy plays a main role in Brain Metastases treatment. Radiomics and Dosiomics, coupled with Machine Learning approaches are emerging in radiation oncology as support in clinical decision-making workflow. In this study a machine learning approach was used to predict the late toxicities induced by Stereotactic Radiotherapy including clinical, radiomics and dosiomics features extracted from patients. Materials and methods Lesions contribution, concomitant and/or sequential treatmen…

Radiomics and dosiomics in radionecrosis prediction in brain metastasis treated with Stereotactic Radiation Therapy: a machine learning approach
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Identifying key risk factors of adolescent Internet Gaming Disorder using explainable machine learning and network analysis

Background Internet Gaming Disorder (IGD) poses significant psychological and social risks for adolescents. Its development involves complex interactions among early adversity, negative life events, psychological symptoms, and regulatory emotional self-efficacy, yet relative importance of these factors and their interrelationships remain incompletely understood. Objective To identify the key demographic and psychosocial factors associated with adolescent IGD, quantify their relative contributions to IGD risk, an…

Identifying key risk factors of adolescent Internet Gaming Disorder using explainable machine learning and network analysis
Health

Predicting early psychiatric readmission among people with major depressive disorder: A machine learning analysis from the prospective multicentre DEEP READ study

Background Major depressive disorder (MDD) is associated with high relapse rates, with around 20% of inpatients experiencing readmission within 90 days after discharge. Routinely collected clinical information may help identify individuals at higher risk of readmission. Machine learning (ML) models could complement more traditional statistical approaches by exploring complex relationships among multiple vulnerability factors. Methods The DEEP READ study is a prospective, multicentre cohort study conducted across…

Predicting early psychiatric readmission among people with major depressive disorder: A machine learning analysis from the prospective multicentre DEEP READ study
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Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC

Despite a decade in, immunotherapy (IO) treatment selection in non-small cell lung cancer (NSCLC) remains largely guided by subgroup analyses and imperfect programmed death ligand 1 (PD-L1) and clinical scores. To our knowledge, I 3 LUNG ( NCT05537922 ) is currently the largest international, real-world, multimodal, artificial intelligence (AI)-based study, enrolling 2,396 patients. We integrated real-world clinical and blood (CB) data, computed tomography (CT) images, digital pathology (DP), and genomics into m…

Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC
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A multi-task learning-based deep learning model for precise estimation of rib fracture age on chest CT

Rib fractures are a common type of chest injury, and the estimation of the fracture age mainly relies on clinical or forensic imaging experts making rough judgments based on CT scans, which is highly subjective. In recent years, artificial intelligence (AI) models have performed exceptionally well in rib fracture detection tasks, providing a potential technical foundation for inferring the time of fracture formation. Therefore, it is necessary to develop deep learning model tools to assist human judgment. In thi…

A multi-task learning-based deep learning model for precise estimation of rib fracture age on chest CT
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Artificial intelligence in laboratory medicine: From machine learning to large language models

Abstract The integration of artificial intelligence (AI) into laboratory medicine has undergone a remarkable evolution over the past decade, shifting from traditional machine learning (ML) applied to structured laboratory data to the recent emergence of large language models (LLMs) capable of processing unstructured clinical text, interpreting complex laboratory findings, and supporting clinical decision-making. This narrative review traces that progression and critically compares four main AI paradigms accessib…

Artificial intelligence in laboratory medicine: From machine learning to large language models