Latest AI and machine learning research in us health policy for healthcare professionals.
Cognitive motor dissociation (CMD) is associated with long-term recovery in acute brain injury, but CMD testing is only available in few centers. Our objective was to identify surface EEG patterns with high sensitivity or positive predictive value (PPV) for CMD in patients with acute disorders of consciousness to refine allocation of this resource-intensive test. In this observational cohort study...
In-context learning enables large language models (LLMs) to perform a variety of tasks, including solving reinforcement learning (RL) problems. Given their potential use as (autonomous) decision-making agents, it is important to understand how these models behave in RL tasks and the extent to which they are susceptible to biases. Motivated by the fact that, in humans, it has been widely documented...
INTRODUCTION: Tuberculous meningitis (TBM) leads to high mortality, especially amongst individuals with HIV. Predicting the incidence of disease-relat...
In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pandemics, there is a need for tools that can address...
Off-policy policy evaluation (OPE) estimates the outcome of a new policy using historical data collected from a different policy. However, existing ...
Despite advances in AI's performance and interpretability, AI advisors can undermine experts' decisions and increase the time and effort experts mus...
Recent advancements in NLP have spurred significant interest in analyzing social media text data for identifying linguistic features indicative of m...
The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis...
Artificial intelligence (AI) and digital public infrastructure (DPI) are two technological developments that have taken center stage in global polic...
The unequal distribution of educational opportunities carries the risk of having a long-term negative impact on general social peace, a country's ec...
Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...
Artificial Intelligence (AI) is transforming diverse societal domains, raising critical questions about its risks and benefits and the misalignments...
Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in av...
In Byzantine Agreement (BA), there is a set of $n$ parties, from which up to $t$ can act byzantine. All honest parties must eventually decide on a c...
Ensuring that generative AI systems align with human values is essential but challenging, especially when considering multiple human values and thei...
Recent advancements in diffusion models trained on large-scale data have enabled the generation of indistinguishable human-level images, yet they of...
Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Disease (ESRD) using machine learning (ML) and deep ...
Public actors are often seen as slow, especially in renewing information systems, due to complex tendering and competition regulations, which delay ...
Fairness in AI-driven decision-making systems has become a critical concern, especially when these systems directly affect human lives. This paper e...
Off-Policy Evaluation (OPE) is employed to assess the potential impact of a hypothetical policy using logged contextual bandit feedback, which is cr...