Latest AI and machine learning research in us health policy for healthcare professionals.
Medicare fraud poses a substantial challenge to healthcare systems, resulting in significant financial losses and undermining the quality of care provided to legitimate beneficiaries. This study investigates the use of machine learning (ML) to enhance Medicare fraud detection, addressing key challenges such as class imbalance, high-dimensional data, and evolving fraud patterns. A dataset compris...
Large Language Models (LLMs) have introduced significant advancements to the capabilities of Natural Language Processing (NLP) in recent years. However, as these models continue to scale in size, memory constraints pose substantial challenge. Key and Value cache (KV cache) quantization has been well-documented as a promising solution to this limitation. In this work, we provide two novel theorem...
Large Language Models (LLMs) employ three popular training approaches: Masked Language Models (MLM), Causal Language Models (CLM), and Sequence-to-S...
First-price auctions are one of the most popular mechanisms for selling goods and services, with applications ranging from display advertising to ti...
Identifying cognitive impairment within electronic health records (EHRs) is crucial not only for timely diagnoses but also for facilitating research...
Drug-side effect research is vital for understanding adverse reactions arising in complex multi-drug therapies. However, the scarcity of higher-orde...
Consistency models (CMs) have shown promise in the efficient generation of both image and text. This raises the natural question of whether we can l...
Guidance in image generation steers models towards higher-quality or more targeted outputs, typically achieved in Diffusion Models (DMs) via Classif...
Large language models (LLMs) have shown impressive capabilities in natural language processing tasks, including dialogue generation. This research a...
AI systems are increasingly tasked to complete responsibilities with decreasing oversight. This delegation requires users to accept certain risks, t...
Multi-UAV air combat is a complex task involving multiple autonomous UAVs, an evolving field in both aerospace and artificial intelligence. This pap...
Medical language models (MLMs) have become pivotal in advancing medical natural language processing. However, prior models that rely on pre-training...
As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited re...
Values or principles are key elements of human society that influence people to behave and function according to an accepted standard set of social ...
When applied in healthcare, reinforcement learning (RL) seeks to dynamically match the right interventions to subjects to maximize population benefi...
The development of flexible bioelectronics remains a complex, multidisciplinary process that demands specialized expertise and labor-intensive efforts...
Value-guided decisions are a cornerstone of cognition, yet the underlying circuit-level mechanisms remain elusive. We used reinforcement learning to t...
Social influence in risky decision-making means changing risky behavior after observing other’s choices. Although attributes’ prioritization can alter...
The advent of Large Language Models (LLMs) has transformed natural language processing and offers new possibilities for analyzing qualitative data in ...
Data, information and knowledge in health care has expanded exponentially over the last 50 years, leading to significant challenges with information o...