Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Many NP-hard graph problems become easy for some classes of graphs, such as coloring is easy for bipartite graphs, but NP-hard in general. So we can ask question like when does a hard problem become easy? What is the minimum substructure for which the problem remains hard? We use the notion of boundary classes to study such questions. In this paper, we introduce a method for transforming the bou...
Combating money laundering has become increasingly complex with the rise of cybercrime and digitalization of financial transactions. Graph-based machine learning techniques have emerged as promising tools for Anti-Money Laundering (AML) detection, capturing intricate relationships within money laundering networks. However, the effectiveness of AML solutions is hindered by data silos within finan...
The real time analysis and secure transmission of electrocardiogram (ECG) signals are critical for ensuring both effective medical diagnosis and pat...
This study introduces the development of a state of the art, real time ECG monitoring and analysis system, incorporating cutting edge medical techno...
Density-equalizing map is a shape deformation technique originally developed for cartogram creation and sociological data visualization on planar ge...
Large Language Model (LLM) Agents are an emerging computing paradigm that blends generative machine learning with tools such as code interpreters, w...
Trusted hardware's freshness guarantee ensures that an adversary cannot replay an old value in response to a memory read request. They rely on maint...
The U.S. Decennial Census serves as the foundation for many high-profile policy decision-making processes, including federal funding allocation and ...
Our work tackles the challenge of securing user inputs in cloud-hosted large language model (LLM) serving while ensuring model confidentiality, outp...
Advances in generative models have created Artificial Intelligence-Generated Images (AIGIs) nearly indistinguishable from real photographs. Leveragi...
Numerical simulation is powerful to study nonlinear solid mechanics problems. However, mesh-based or particle-based numerical methods suffer from th...
Medical image segmentation, a critical application of semantic segmentation in healthcare, has seen significant advancements through specialized com...
Dentists, especially those who are not oral lesion specialists and live in rural areas, need an artificial intelligence (AI) system for accurately ass...
Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) presents significant privacy and security challen...
This study explores the potential of federated learning (FL) to develop a predictive model of hypoxemia in intensive care unit (ICU) patients. Central...
Research on smooth vector graphics is separated into two independent research threads: one on interpolation-based gradient meshes and the other on d...
Evaluating the behavioral boundaries of deep learning (DL) systems is crucial for understanding their reliability across diverse, unseen inputs. Exi...
The generalized winding number is an essential part of the geometry processing toolkit, allowing to quantify how much a given point is inside a surf...
Electronic Health Records (EHRs) and Medical Data are classified as personal data in every privacy law, meaning that any related service that includ...
Community-based palliative care is a useful, but underutilized service to support seriously ill older adults to remain safely at home and improve qual...