+ 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…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
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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…

Annals of Translational Medicine · Health

Beyond the algorithm: health technology assessment frameworks for AI in cardiology under the European Union Health Technology Assessment Regulation: a systematic review
Triage safety of patient-facing AI chatbots for nipple discharge: A guideline-informed assessment of red-flag recognition and patient actionability
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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
Quantifying the impact of slice thickness on cardiovascular risk stratification in lung cancer screening: a multi-center "RESCUE" study
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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
Embedded transparency in artificial intelligence: a prerequisite for equity and representation in AI-enabled clinical trials
Model-prefilled problem

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
Performance evaluation of domain-specific and general-purpose AI models for chest radiograph interpretation: a comparative study
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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
Seeing beyond the algorithm: artificial intelligence and the enduring role of the radiologist
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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
Adopting AI Enhances Humanitarian Operations While Demanding Critical Trade-Offs
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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

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

Artificial Intelligence-Based CTA Software for Real-World Detection of Large Vessel Occlusion in Acute Ischemic Stroke

Background and purpose Artificial intelligence (AI)-based tools for CT angiography (CTA) have been introduced to support rapid detection of large vessel occlusion (LVO) in acute ischemic stroke. Although regulatory approval has relied mainly on controlled clinical studies, evidence from routine clinical practice remains limited. This study aimed to assess the real-world diagnostic performance and workflow impact of the Brainomix e-CTA software. Materials and methods We conducted a retrospective, single-center ob…

Health
Artificial Intelligence-Based CTA Software for Real-World Detection of Large Vessel Occlusion in Acute Ischemic Stroke

Machine learning prediction of local control after Gamma Knife radiosurgery to post-resection cavities from brain metastases: a proof-of-concept study

Background Large symptomatic brain metastases require initial surgical resection. However, local control (LC) after Gamma Knife radiosurgery (GKRS) to resection cavities remains variable. Quantitative risk stratification using routinely available treatment-time variables could inform surveillance and multidisciplinary decision-making. Methods We performed a retrospective study of post-resection cavities treated with GKRS at a single institution (2014-2024). The primary endpoint was LC. The cohort comprised of 40…

Health
Machine learning prediction of local control after Gamma Knife radiosurgery to post-resection cavities from brain metastases: a proof-of-concept study

Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization

BACKGROUND: Insertable cardiac monitors (ICMs) are essential for managing arrhythmias but often generate large numbers of transmissions and false alerts. Integrating artificial intelligence (AI) as part of the ICM workflow can reduce this burden. However, its impact on clinic workflow and resource utilization must be better understood. OBJECTIVES: The aim of the study was to assess the impact of AI-enhanced ICMs on clinic workflow and resource utilization. METHODS: A cross-sectional analysis was conducted using…

Health
Impact of Artificial Intelligence-Enhanced Insertable Cardiac Monitors on Device Clinic Workflow and Resource Utilization

From severity scoring to predictive analytics: the emerging role of AI in neurosurgery

The rapid integration of artificial intelligence (AI) into neurosurgical practice is transforming every phase of patient care from diagnostic imaging and preoperative planning to intraoperative decision-making and postoperative management. This narrative review traces the evolution of data-driven neurosurgery, beginning with traditional severity scoring systems and advancing toward predictive analytics and intelligent automation. By examining structured data (such as electronic health records and laboratory valu…

Health
From severity scoring to predictive analytics: the emerging role of AI in neurosurgery

An analysis of the real world performance of an artificial intelligence based autism diagnostic

Rapidly rising demand for pediatric autism evaluations has outpaced specialist capacity and created a crisis of delayed diagnoses and treatment. Streamlining the diagnostic process could reduce wait times and optimize use of limited specialist resources. Following strong clinical trial results, Canvas Dx, an AI-based diagnostic, was FDA authorized to support accurate diagnosis or rule-out of autism in children 18-72 months with caregiver or healthcare provider concern for developmental delay. To gain insight int…

Health
An analysis of the real world performance of an artificial intelligence based autism diagnostic

Reproducibility and Validation Challenges in AI-Driven Scaffold Design for Bone Regeneration

Artificial intelligence (AI) is increasingly applied to bioink formulation and bioprinting process control in tissue engineering (TE). Yet, translational progress remains constrained by small datasets, limited cross-platform validation, and weak links between computational predictions and biological outcomes. This review critically evaluates experimentally validated AI applications across scaffold-based bone regeneration, spanning materials design, fabrication control, and biological assessment. Physics-informed…

Health
Reproducibility and Validation Challenges in AI-Driven Scaffold Design for Bone Regeneration