Latest AI and machine learning research in ethics for healthcare professionals.
Automation and AI-driven decision support systems are increasingly reshaping healthcare, particularly in diagnostic and clinical management contexts. Although their potential to enhance access, efficiency and personalisation is widely recognised, there remain ethical concerns especially around the shifting dynamics of healthcare relationships. This article proposes a conceptual framework for under...
Telesurgery, or remote surgery, represents a transformative fusion of medicine and technology, enabling surgeons to perform procedures on patients located miles away using robotic systems and advanced telecommunications. However, its widespread adoption remains limited, with fewer than 50 documented fully remote telesurgical procedures in the past two decades. While robotic-assisted surgery is inc...
The integration of artificial intelligence in nursing practice presents significant ethical challenges that require a comprehensive assessment framewo...
Although still limited, the integration of artificial intelligence (AI) in health care has rapidly expanded in the past few years, especially in oncol...
As machine learning systems are increasingly deployed in high-stakes domains such as criminal justice, finance, and healthcare, the demand for inter...
Alternating Current Optimal Power Flow (AC-OPF) aims to optimize generator power outputs by utilizing the non-linear relationships between voltage m...
Artificial Intelligence (AI) is transforming sectors such as healthcare, finance, and autonomous systems, offering powerful tools for innovation. Ye...
As generative AI systems become widely adopted, they enable unprecedented creation levels of synthetic data across text, images, audio, and video mo...
The automated generation of radiology reports from chest X-ray images holds significant promise in enhancing diagnostic workflows while preserving p...
Artificial Knowledge (AK) systems are transforming decision-making across critical domains such as healthcare, finance, and criminal justice. Howeve...
This paper introduces ADEPT, a system using Large Language Model (LLM) personas to simulate multi-perspective ethical debates. ADEPT assembles panel...
Mistaken eyewitness identification is one of the leading causes of false convictions. Improving law enforcement's ability to identify correct identifi...
Although popularized AI fairness metrics, e.g., demographic parity, have uncovered bias in AI-assisted decision-making outcomes, they do not conside...
Unsupervised pathology detection trains models on non-pathological data to flag deviations as pathologies, offering strong generalizability for iden...
Exploring the time-resolved dynamics of neurochemicals is essential for deciphering neuronal functions, intercellular communication, and neurophysiolo...
Ethical theories and Generative AI (GenAI) models are dynamic concepts subject to continuous evolution. This paper investigates the visualization of...
We present a comprehensive analysis of the digest2 parameters for candidates of the Near-Earth Object Confirmation Page (NEOCP) that were reported b...
Large multimodal models (LMMs) now excel on many vision language benchmarks, however, they still struggle with human centered criteria such as fairn...
In radiology and other medical fields, informed consent often rely on paper-based forms, which can overwhelm patients with complex terminology. These ...
This study explores the utility of Large Language Models (LLMs) to support finding rare patient record details that could make a patient identifiable....