Latest AI and machine learning research in ethics for healthcare professionals.
Large-scale machine learning (ML) models are increasingly being used in critical domains like education, lending, recruitment, healthcare, criminal justice, etc. However, the training, deployment, and utilization of these models demand substantial computational resources. To decrease computation and memory costs, machine learning models with sparse weight matrices are widely used in the literatu...
Ensuring transparency in machine learning decisions is critically important, especially in sensitive sectors such as healthcare, finance, and justice. Despite this, some popular explainable algorithms, such as Local Interpretable Model-agnostic Explanations (LIME), often produce unstable explanations due to the random generation of perturbed samples. Random perturbation introduces small changes ...
The question of how to make decisions that maximise the well-being of all persons is very relevant to design language models that are beneficial to ...
Accurate tropical cyclone (TC) intensity prediction is crucial for mitigating storm hazards, yet its complex dynamics pose challenges to traditional...
Artificial intelligence (AI) is transforming healthcare by enhancing clinical decision-making, particularly in nursing, where it supports tasks such a...
In the face of intensified datafication and automation in public sector industries, frameworks like design justice and the feminist practice of refu...
Large language models (LLMs) demonstrate significant potential in advancing medical applications, yet their capabilities in addressing medical ethic...
Context: Dark patterns are user interface or other software designs that deceive or manipulate users to do things they would not otherwise do. Even ...
The rapid advancement of generative AI has enabled the creation of pre-mortem digital twins, AI-driven replicas that mimic the behavior, personality...
Over the past decade, the Table Union Search (TUS) task has aimed to identify unionable tables within data lakes to improve data integration and dis...
Fast and accurate estimation of quantiles on data streams coming from communication networks, Internet of Things (IoT), and alike, is at the heart o...
The analytic characterization of the high-dimensional behavior of optimization for Generalized Linear Models (GLMs) with Gaussian data has been a ce...
Neurofibromatosis Type 1 is a genetic disorder characterized by the development of neurofibromas (NFs), which exhibit significant variability in siz...
As artificial intelligence (AI) technologies begin to permeate diverse fields-from healthcare to education-consumers, researchers and policymakers a...
Fairness is a fundamental principle in medical ethics. Vision Language Models (VLMs) have shown significant potential in the medical field due to th...
Computational notebooks are the de facto platforms for exploratory data science, offering an interactive programming environment where users can cre...
Survival analysis, a vital tool for predicting the time to event, has been used in many domains such as healthcare, criminal justice, and finance. L...
Resting-state functional magnetic resonance imaging (rs-fMRI) and its derived functional connectivity networks (FCNs) have become critical for under...
Multimodal fusion leverages information across modalities to learn better feature representations with the goal of improving performance in fusion-b...
Artificial intelligence (AI) has the potential to standardize and automate important aspects of fertility treatment, improving clinical outcomes. One ...