Medicare

Learning Efficient Robotic Garment Manipulation with Standardization

Garment manipulation is a significant challenge for robots due to the complex dynamics and potential self-occlusion of garments. Most existing methods of efficient garment unfolding overlook the crucial role of standardization of flattened garments, which could significantly simplify downstream tasks like folding, ironing, and packing. This paper presents APS-Net, a novel approach to garment man...

Interactive Multi-Objective Probabilistic Preference Learning with Soft and Hard Bounds

High-stakes decision-making involves navigating multiple competing objectives with expensive evaluations. For instance, in brachytherapy, clinicians must balance maximizing tumor coverage (e.g., an aspirational target or soft bound of >95% coverage) against strict organ dose limits (e.g., a non-negotiable hard bound of <601 cGy to the bladder), with each plan evaluation being resource-intensive....

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning

High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual...

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy

Purpose: In high-dose-rate (HDR) prostate brachytherapy procedures, the pattern of needle placement solely relies on physician experience. We invest...

Where Journalism Silenced Voices: Exploring Discrimination in the Representation of Indigenous Communities in Bangladesh

In this paper, we examine the intersections of indigeneity and media representation in shaping perceptions of indigenous communities in Bangladesh. ...

CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray

The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges i...

Enhanced Trust Region Sequential Convex Optimization for Multi-Drone Thermal Screening Trajectory Planning in Urban Environments

The rapid detection of abnormal body temperatures in urban populations is essential for managing public health risks, especially during outbreaks of...

Conformal coronary calcification volume estimation with conditional coverage via histogram clustering

Incidental detection and quantification of coronary calcium in CT scans could lead to the early introduction of lifesaving clinical interventions. H...

Enhancing Interpretable Image Classification Through LLM Agents and Conditional Concept Bottleneck Models

Concept Bottleneck Models (CBMs) decompose image classification into a process governed by interpretable, human-readable concepts. Recent advances i...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field....

Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline

Lightweight long-range mapping is critical for safe navigation of UAV swarms in large-scale unknown environments. Traditional stereo vision systems ...

LoHoVLA: A Unified Vision-Language-Action Model for Long-Horizon Embodied Tasks

Real-world embodied agents face long-horizon tasks, characterized by high-level goals demanding multi-step solutions beyond single actions. Successf...

S3CE-Net: Spike-guided Spatiotemporal Semantic Coupling and Expansion Network for Long Sequence Event Re-Identification

In this paper, we leverage the advantages of event cameras to resist harsh lighting conditions, reduce background interference, achieve high time re...

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...

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...

Deep Learning-Based BMD Estimation from Radiographs with Conformal Uncertainty Quantification

Limited DXA access hinders osteoporosis screening. This proof-of-concept study proposes using widely available knee X-rays for opportunistic Bone Mi...

Risk-Sensitive Conformal Prediction for Catheter Placement Detection in Chest X-rays

This paper presents a novel approach to catheter and line position detection in chest X-rays, combining multi-task learning with risk-sensitive conf...

Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries

While large language models (LLMs) are increasingly capable of handling longer contexts, recent work has demonstrated that they exhibit the "lost in...

Learning to See More: UAS-Guided Super-Resolution of Satellite Imagery for Precision Agriculture

Unmanned Aircraft Systems (UAS) and satellites are key data sources for precision agriculture, yet each presents trade-offs. Satellite data offer br...

Frame-Level Captions for Long Video Generation with Complex Multi Scenes

Generating long videos that can show complex stories, like movie scenes from scripts, has great promise and offers much more than short clips. Howev...