Ethics

Model-informed approach to estimate treatment effect in placebo-controlled clinical trials using an artificial intelligence-based propensity weighting methodology to account for non-specific responses to treatment.

In randomized, placebo controlled clinical trials (RCT) in major depressive disorders (MDD), treatment response (TR) is estimated by the change from baseline at study-end (EOS) of the scores of clinical scales used for assessing disease severity. Treatment effect (TE) is estimated by the baseline-adjusted difference at EOS of TR between active treatments and placebo.The TE is function of treatment...

Revolutionizing healthcare: a comparative insight into deep learning's role in medical imaging.

Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alzeheimer Disease (AD), a prevalent form of dementia, uses Magnetic Resonance Imaging (MRI) scans, which is then analysed via DL models. To address the model computational constraints, Cloud Computing (CC) is integrated to operate with the DL models. Recent articles on DL-based MRI have not discussed ...

Three-Dimensional Thermal Tomography with Physics-Informed Neural Networks.

: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imagi...

Regulating professional ethics in a context of technological change.

BACKGROUND: Technological change is impacting the work of health professionals, especially with recent developments in artificial intelligence. Resear...

Machine learning identifies cytokine signatures of disease severity and autoantibody profiles in systemic lupus erythematosus - a pilot study.

Disrupted cytokine networks and autoantibodies play an important role in the pathogenesis of systemic lupus erythematosus. However, conflicting report...

Machine learning approaches for predicting and diagnosing chronic kidney disease: current trends, challenges, solutions, and future directions.

Chronic Kidney Disease (CKD) represents a significant global health challenge, contributing to increased morbidity and mortality rates. This review pa...

Digital Doppelgängers and Lifespan Extension: What Matters?

There is an ongoing debate about the ethics of research on lifespan extension: roughly, using medical technologies to extend biological human lives be...

Using AI to Predict Patients' Length of Stay: PACU Staff's Needs and Expectations for Developing and Implementing an AI System.

The need for innovative technology in healthcare is apparent due to challenges posed by the lack of resources. This study investigates the adoption o...

Modification and Validation of the System Causability Scale Using AI-Based Therapeutic Recommendations for Urological Cancer Patients: A Basis for the Development of a Prospective Comparative Study.

The integration of artificial intelligence, particularly Large Language Models (LLMs), has the potential to significantly enhance therapeutic decision...

Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.

The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exceptio...

Enabling Demonstrated Consent for Biobanking with Blockchain and Generative AI.

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential u...

Design of a Trustworthy Cloud-Native National Digital Health Information Infrastructure for Secure Data Management and Use.

Since 2022, Malawi Ministry of Health (MoH) designated the development of a National Digital Health Information System (NDHIS) as one of the most impo...

A protocol for trustworthy EEG decoding with neural networks.

Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their hi...

Mapping Spatiotemporal Disparities in Residential Electricity Inequality Using Machine Learning.

The move toward electrification is critical for decarbonizing the energy sector but may exacerbate energy unaffordability without proper safeguards. A...

Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems.

We introduce a method for training exactly conservative physics-informed neural networks and physics-informed deep operator networks for dynamical sys...

Neonatal bioethics, AI, and genomics.

Artificial intelligence (AI) and synthetic biology will transform civilization. The only question is how. In this paper, I explore some recent develop...

Federated learning-based prediction of depression among adolescents across multiple districts in China.

Depression in adolescents is a serious mental health condition that can affect their emotional and social well-being. Detailed understanding of depres...

Justice-centered best practices for accessibility to public buildings in a tier II city: Insights from a Delphi expert consensus.

BACKGROUND: Despite beneficial progress in policies, awareness and advocacy, accessibility gaps exist in public buildings in India. Challenges achievi...

Potential promises and perils of artificial intelligence in psychotherapy -The AI Psychotherapist (APT).

OBJECTIVE: Since the release of ChatGPT, popular demand has driven the use of social chatbots as pseudo-AI psychotherapists. With time, it is inevitab...

Safeguarding Patients in the AI Era: Ethics at the Forefront of Pharmacovigilance.

Artificial intelligence is increasingly being used in pharmacovigilance. However, the use of artificial intelligence in pharmacovigilance raises ethic...