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1045 published stories · page 52 of 70

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Improving turnaround times with artificial intelligence in microbiology

This dual-center study evaluated the impact of artificial intelligence (AI) on urine culture turnaround times in Canadian diagnostic laboratories using microbiology laboratory automation. Data were collected before and after the implementation of PhenoMATRIX (PM), an AI-based software that provides continuous culture sorting and result interpretation support. In both a low-volume tertiary care hospital and a high-volume community laboratory, PM enabled earlier availability of interpretable results; however, redu…

Journal of Clinical Microbiology · Health

Improving turnaround times with artificial intelligence in microbiology

Both readings

Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis

Background: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by bone fragility and recurrent fractures. Emerging biologics demonstrate promise by targeting bone-remodeling pathways, yet evidence for their efficacy and safety remains fragmented and heterogeneous, and no prior systematic review in OI has incorporated artificial intelligence (AI) to synthesize it. Objective: This study aims to systematically evaluate the efficacy and safety of novel biologics in patients with OI using an AI-ass…

Health

Model-prefilled problem

Signs of psychosis seen in Australian users’ interactions with AI chatbots, expert warns

A leading AI expert has warned some Australians are showing signs of psychosis or mania in their interactions with chatbots, arguing Silicon Valley is being “careless” with the technology amid a pursuit of profit. During an address at the National Press Club on Wednesday, Toby Walsh, scientia professor of artificial intelligence at the University of New South Wales, said he believed the AI race will be both “boom and doom”, with some benefits. But his speech – a copy of which was provided to Guardian Australia –…

Other

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Preparing students for a world shaped by artificial intelligence | Letters

Prof Leo McCann and Prof Simon Sweeney are right to warn that uncritical reliance on artificial intelligence risks bypassing deep learning (Letters, 16 September). But that does not mean large language models have no place in higher education. Used thoughtfully, they can enhance teaching and learning. Graduates will enter a workforce where AI is ubiquitous. To exclude it from education is to send students out unprepared. The task is not to ignore AI, but to teach students how to use it critically. AI can also re…

Other

Model-prefilled problem

Brady Tkachuk decries White House’s AI video of him insulting Canadians after US gold

US ice hockey star Brady Tkachuk has said he does not appreciate an AI video released by the White House that shows him insulting Canadians. Tkachuk played in the Americans’ victory over Canada at the Winter Olympics on Sunday, which secured the US men their first gold medal since 1980. In the wake of that win, the White House’s TikTok account published video of Tkachuk saying: “They booed our national anthem, so I had to come out and teach those maple syrup eating fuckers a lesson.” Tkachuk never said those wor…

Sports

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Beyond EuroSCORE II: is artificial intelligence ready to redefine risk stratification in cardiothoracic surgery?

Risk stratification is central to contemporary cardiothoracic surgical practice, guiding patient selection, perioperative planning, informed consent, and benchmarking of outcomes across institutions. Established models such as European System for Cardiac Operative Risk Evaluation II and the Society of Thoracic Surgeons risk score remain widely used because they are validated, interpretable, and embedded within routine clinical workflows. However, their static structure and reliance on predefined variables may li…

Health

Model-prefilled problem

Beyond the algorithm: health technology assessment frameworks for AI in cardiology under the European Union Health Technology Assessment Regulation: a systematic review

Background: Artificial intelligence (AI) is increasingly used in cardiovascular care to support diagnosis, monitoring and clinical decision-making. However, its dynamic and adaptive nature challenges conventional health technology assessment (HTA) frameworks, which are typically designed for static interventions. This review aims to assess how existing literature supports HTA-relevant evaluation of AI-based cardiovascular technologies and examine their alignment with the evidentiary requirements outlined in the…

Health

Triage safety of patient-facing AI chatbots for nipple discharge: A guideline-informed assessment of red-flag recognition and patient actionability

Objective To evaluate red-flag recognition, clinical safety, and the quality of patient actionability in responses generated by artificial intelligence (AI) chatbots to patient questions about nipple discharge. Methods This guideline-informed cross-sectional evaluation was conducted to assess the performance of AI chatbots in simulated nipple discharge consultations. A total of 36 English-language simulated patient questions were developed on the basis of clinical guidelines and real-world consultation scenarios…

Health

Triage safety of patient-facing AI chatbots for nipple discharge: A guideline-informed assessment of red-flag recognition and patient actionability

Quantifying the impact of slice thickness on cardiovascular risk stratification in lung cancer screening: a multi-center "RESCUE" study

Background: Patients undergoing routine non-gated chest computed tomography (CT) for health checkups or atypical chest discomfort often present with a coronary artery calcium (CAC) score of zero on standard 5.0 mm reconstructions. We hypothesized that these thick slices obscure mild calcification due to partial volume effects (PVEs), which could be recovered by retrospective analysis of native thin-slice images. This study aimed to quantify the rate of unrecognized coronary calcification on standard thick-slice…

Health

Quantifying the impact of slice thickness on cardiovascular risk stratification in lung cancer screening: a multi-center "RESCUE" study

Embedded transparency in artificial intelligence: a prerequisite for equity and representation in AI-enabled clinical trials

Artificial intelligence is being embedded in clinical trial infrastructure, shaping who is identified, stratified, and analysed. Opaque models risk amplifying existing disparities in the evidence base. We argue that embedded transparency, the structural integration of ex ante interpretability, demographic auditability, documented uncertainty handling, and stakeholder-relative explanation, is a necessary, though not sufficient, condition for equitable AI-enabled trials, and propose governance recommendations acti…

Health

Embedded transparency in artificial intelligence: a prerequisite for equity and representation in AI-enabled clinical trials

Performance evaluation of domain-specific and general-purpose AI models for chest radiograph interpretation: a comparative study

Chest radiography remains the most widely used imaging modality worldwide; however, its interpretation is inherently challenging because of overlapping anatomical structures and subtle findings. Recent advances in multimodal large language models (LLMs) have enabled automated radiology report generation, yet their clinical performance relative to domain-specific medical AI systems remains insufficiently validated. This study aimed to evaluate the performance and clinical applicability of a domain-specific multim…

Health

Performance evaluation of domain-specific and general-purpose AI models for chest radiograph interpretation: a comparative study

Seeing beyond the algorithm: artificial intelligence and the enduring role of the radiologist

Artificial intelligence (AI) has rapidly emerged as a transformative force in radiology, offering enhanced diagnostic accuracy, workflow optimization, and the potential to alleviate rising imaging demands. As radiology remains inherently dependent on pattern recognition and high-volume data interpretation, it represents an ideal domain for AI integration. This narrative review synthesizes current evidence on the clinical impact of AI across multiple dimensions of radiologic practice, including diagnostic perform…

Health

Seeing beyond the algorithm: artificial intelligence and the enduring role of the radiologist

Adopting AI Enhances Humanitarian Operations While Demanding Critical Trade-Offs

Artificial intelligence (AI) is increasingly impacting the cooperation sector, transforming how humanitarians are operating in the field. AI tools now allow for improved health diagnostics and quality services. In conflict areas, organizations are able to improve the efficiency of their analysis, and propose optimized data management processes for more multifactorial predictions. In a context where human and financial resources are limited, AI address the gaps to sustain emergency responses. In this commentary,…

Health

Adopting AI Enhances Humanitarian Operations While Demanding Critical Trade-Offs

A Nurse Hackathon: Improving Effective and Timely Nurse Handoffs Through Use of Generative Artificial Intelligence

Effective handoff communication between the emergency department and inpatient units is essential for patient safety and nurse well-being. This project uses an innovative design strategy and generative artificial intelligence to improve the quality and consistency of information exchanged during nurse-to-nurse handoffs. By generating computer-based summaries, key patient details can be accurately conveyed, reducing the need for manual review and customization. Developed through a collaborative hackathon with fro…

Health

A Nurse Hackathon: Improving Effective and Timely Nurse Handoffs Through Use of Generative Artificial Intelligence

Custom GPT models for complex rheumatology systematic reviews: A two-part evaluation of data extraction and prognosis appraisal

Background: Systematic reviews are essential for evidence-based practice but remain resource-intensive, particularly during full-text data extraction and structured risk-of-bias appraisal in prognostic research. These challenges are amplified in complex autoimmune diseases such as systemic lupus erythematosus (SLE). Recent advances in large language models (LLMs) have raised interest in their potential; however, rigorous benchmarking against expert reviewers in real-world rheumatology settings is limited. Object…

Health

Custom GPT models for complex rheumatology systematic reviews: A two-part evaluation of data extraction and prognosis appraisal