Latest AI and machine learning research in ethics for healthcare professionals.
Background Prognosis and therapeutic management in Parkinson's disease is a challenging task by its highly heterogeneous disease progression and symptoms presentation, lacking biomarkers to predict individual disease trajectories. Objective To determine whether baseline blood transcriptomes, analyzed through biologically defined pathway gene sets, contain signatures that distinguish distinct motor...
The rapid deployment of deep neural network (DNN) accelerators in safety-critical domains such as autonomous vehicles, healthcare systems, and financial infrastructure necessitates robust mechanisms to safeguard data confidentiality and computational integrity. Existing security solutions for DNN accelerators, however, suffer from excessive hardware resource demands and frequent off-chip memory ac...
Accurate splice site prediction is fundamental to understanding gene expression and its associated disorders. However, most existing models are biased...
Training a neural network requires navigating a high-dimensional, non-convex loss surface to find parameters that minimize this loss. In many ways, it...
Background and Objective: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent o...
Magnetoencephalography (MEG) forward and inverse modeling is fundamental to neuroscientific discovery, yet the inversion of partial differential equat...
Background: Generating synthetic data using artificial intelligence, such as large language models (LLMs), is a useful strategy in public health becau...
Determining physiological stress at high resolution is crucial across diverse settings to enable informed decision-making in the context of health and...
Coronary microvascular dysfunction (CMD) affects millions worldwide yet remains underdiagnosed because gold-standard physiological measurements are in...
Federated learning aggregates model updates from distributed clients, but standard first order methods such as FedAvg apply the same scalar weight to ...
The Pathology Informatics Bootcamp is held annually at the Pathology Informatics Summit and provides pathology trainees with knowledge about both core...
The deployment of biased machine learning (ML) models has resulted in adverse effects in crucial sectors such as criminal justice and healthcare. To...
AI-based judicial assistance and case prediction have been extensively studied in criminal and civil domains, but remain largely unexplored in consu...
The integration of artificial intelligence (AI) in medical imaging raises crucial ethical concerns at every stage of its development, from data coll...
Small- and medium-sized manufacturers need innovative data tools but, because of competition and privacy concerns, often do not want to share their ...
Artificial intelligence (AI) offers incredible possibilities for patient care, but raises significant ethical issues, such as the potential for bias...
Sepsis is a life-threatening disease caused by the dysregulation of the immune response. It is important to identify influential genes modulating the ...
Artificial intelligence (AI) is one of the world's most resource-intensive digital technologies, but the environmental impact of AI on health remains ...
Plastic surgery, by nature an innovative discipline, has historically relied on clinical case reports to advance its techniques. Often unique, these c...
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality ...