Health Policy

An immunohistochemistry-based classification of colorectal cancer resembling the consensus molecular subtypes using convolutional neural networks.

Colorectal cancer (CRC) represents a major global disease burden with nearly 1 million cancer-related deaths annually. TNM staging has served as the foundation for predicting patient prognosis, despite variation across staging groups. The consensus molecular subtype (CMS) is a transcriptome-based system classifying CRC tumors into four subtypes with different characteristics: CMS1 (immune), CMS2 (...

State Estimation and Control of Dynamic Systems from High-Dimensional Image Data

Accurate state estimation is critical for optimal policy design in dynamic systems. However, obtaining true system states is often impractical or infeasible, complicating the policy learning process. This paper introduces a novel neural architecture that integrates spatial feature extraction using convolutional neural networks (CNNs) and temporal modeling through gated recurrent units (GRUs), en...

Digital twins enable full-reference quality assessment of photoacoustic image reconstructions

Quantitative comparison of the quality of photoacoustic image reconstruction algorithms remains a major challenge. No-reference image quality measur...

Transaction Proximity: A Graph-Based Approach to Blockchain Fraud Prevention

This paper introduces a fraud-deterrent access validation system for public blockchains, leveraging two complementary concepts: "Transaction Proximi...

Towards a Generalizable Bimanual Foundation Policy via Flow-based Video Prediction

Learning a generalizable bimanual manipulation policy is extremely challenging for embodied agents due to the large action space and the need for co...

Regulation of artificial intelligence in Uganda's healthcare: exploring an appropriate regulatory approach and framework to deliver universal health coverage.

BACKGROUND: Uganda, like other United Nations (UN) member states, has undertaken to achieve Universal Health Coverage (UHC) by 2030 in line with Susta...

The integrated fuzzy AHP and fuzzy logic techniques for mapping and prioritizing groundwater potential zone based on water quality.

Groundwater, which is utilized to supply water demand in various sectors such as domestic water consumption, agriculture, and industry, could be achie...

Bridging the Gap: Enhancing Digital Accessibility for Medicaid Populations in Telehealth Adoption

The swift evolution of telehealth has revolutionized how medical professionals deliver healthcare services and boost convenience and accessibility. ...

Searching Neural Architectures for Sensor Nodes on IoT Gateways

This paper presents an automatic method for the design of Neural Networks (NNs) at the edge, enabling Machine Learning (ML) access even in privacy-s...

Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models

Enhancing the reasoning capabilities of large language models effectively using reinforcement learning (RL) remains a crucial challenge. Existing ap...

Energy-Efficient QoS-Aware Scheduling for S-NUCA Many-Cores

Optimizing performance and energy efficiency in many-core processors, especially within Non-Uniform Cache Access (NUCA) architectures, remains a cri...

Can Large Language Models Match the Conclusions of Systematic Reviews?

Systematic reviews (SR), in which experts summarize and analyze evidence across individual studies to provide insights on a specialized topic, are a...

Text2Grad: Reinforcement Learning from Natural Language Feedback

Traditional RLHF optimizes language models with coarse, scalar rewards that mask the fine-grained reasons behind success or failure, leading to slow...

Reasoning Is Not All You Need: Examining LLMs for Multi-Turn Mental Health Conversations

Limited access to mental healthcare, extended wait times, and increasing capabilities of Large Language Models (LLMs) has led individuals to turn to...

Refining Few-Step Text-to-Multiview Diffusion via Reinforcement Learning

Text-to-multiview (T2MV) generation, which produces coherent multiview images from a single text prompt, remains computationally intensive, while ac...

Does Rationale Quality Matter? Enhancing Mental Disorder Detection via Selective Reasoning Distillation

The detection of mental health problems from social media and the interpretation of these results have been extensively explored. Research has shown...

MedDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support

Timely and personalized treatment decisions are essential across a wide range of healthcare settings where patient responses vary significantly and ...

Modeling Beyond MOS: Quality Assessment Models Must Integrate Context, Reasoning, and Multimodality

This position paper argues that Mean Opinion Score (MOS), while historically foundational, is no longer sufficient as the sole supervisory signal fo...

Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.

The rapid advancement of Machine Learning (ML) and Deep Learning (DL) technologies has revolutionized healthcare, particularly in the domains of disea...

Evaluation of spatial visual perception of streets based on deep learning and spatial syntax.

Street visual quality improvement plays an important role in urban development. An important direction for street quality research lies in accurately ...