Ethics

Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.

OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This study introduces auto-LSN, an artificial intelligence (AI)-based algorithm for fully automated LSN quantification, assesses its association with fibrosis stage and its non-inferiority in diagnostic performance for advanced chronic liver disease (ACLD) and cirrhosis compared to the FDA-approved, sem...

Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting.

Artificial intelligence (AI) is increasingly used to support medical interpreting and public health communication, yet current systems introduce serious risks to accuracy, confidentiality, and equity, particularly for speakers of low-resource languages. Automatic translation models often struggle with regional varieties, figurative language, culturally embedded meanings, and emotionally sensitive ...

Improving the management and outcomes of preschool wheeze: protocol of a prospective multicentre cohort study.

INTRODUCTION: Preschool wheeze and asthma are associated with substantial morbidity and impaired future lung function. Yet, wheeze is unreliably repor...

Linking Electronic Health Records for Multiple Sclerosis Research: Comparative Study of Deterministic, Probabilistic, and Machine Learning Linkage Methods.

BACKGROUND: Data linkage in pharmacoepidemiological research is commonly employed to ascertain exposures and outcomes or to obtain additional informat...

Protocol for Personalised Prediction of Persistent Postsurgical Pain.

INTRODUCTION: Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and ...

HappyMums mobile application study protocol: use of a smartphone application to gather data predictive of antenatal depression.

INTRODUCTION: Mobile health (mHealth) technologies have become increasingly popular for monitoring mental health symptoms and lifestyle behaviours, an...

Forensic Transcriptomics: Research Progress of the Past Two Decades.

Over the last two decades, advancements in sequencing technology and data science have significantly deepened the study of transcriptomics, especially...

Artificial intelligence in psychiatry: A global perspective on research status, trends and clinical applications.

Artificial intelligence is increasingly used in psychiatric research, yet progress in clinical use and equitable benefit remains uneven. We analyzed 2...

Large Language Model-Assisted Research Question Development in Public Health: A Case Study in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).

OBJECTIVE: To assess the feasibility of using large language models (LLMs) to develop research questions about changes to the Special Supplemental Nut...

Ethical and Bioethical Issues in Physical Therapy: A Systematic Scoping Review.

IMPORTANCE: Ethical and bioethical issues are central to the identity and practice of physical therapy. A comprehensive overview of how these issues a...

Protocol for the PROSECCA study: a new approach for predicting radiotherapy outcome using artificial intelligence and electronic population-based healthcare data.

INTRODUCTION: Within the UK there are 33 deaths every day from prostate cancer, second only to lung cancer as the most common cause of cancer death in...

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation.

BACKGROUND: Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, base...

Moving toward equitable juvenile justice risk assessments for adolescents: Considering clinical, community, and statistical fairness.

Risk assessments are often mandated within the juvenile justice system (JJS). Yet, it is unclear whether these protocols reflect equitable clinical to...

At the Crossroads of Data Justice and Data Capitalism: How Generative AI in Healthcare Mobilises Its Assemblages.

Algorithmic technologies such as machine learning, generative artificial intelligence (GenAI) and automated decision-making have become one of the fro...

Ethics Education in Neonatology: Integrating Theory, Multimodal Methods, and AI Innovation.

This review examines current approaches to ethics education in neonatal-perinatal medicine (NPM), integrating adult learning theory, diverse teaching ...

Exploring service user attitudes towards mental health technologies.

OBJECTIVES: Understanding service users' knowledge of and attitudes towards the rapidly progressing field of mental health technology (MHT) is an impo...

Padé Neurons for Efficient Neural Models.

Neural networks commonly employ the McCulloch-Pitts neuron model, which is a linear model followed by a point-wise non-linear activation. Various rese...

Assessing the Evolution and Influence of Medical Open Databases on Biomedical Research and Health Care Innovation: A 25-Year Perspective With a Focus on Privacy and Privacy-Enhancing Technologies.

The integration of medical open databases with artificial intelligence (AI) technologies marks a transformative era in biomedical research and health ...

Ethical Knowledge, Challenges, and Institutional Strategies Among Medical AI Developers and Researchers: Focus Group Study.

BACKGROUND: As artificial intelligence (AI) becomes increasingly embedded in clinical decision-making and preventive care, it is urgent to address eth...

Ethics in the World of Artificial Intelligence.

Across health care, traditional principles of biomedical ethics (autonomy, beneficence, nonmaleficence, and justice) form a base expectation for the u...