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Medical Ethics / Professional Responsibility

Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.

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Showing 701-720 of 6,010 articles

Enhancing Shape Perception and Segmentation Consistency for Industrial Image Inspection

Semantic segmentation stands as a pivotal research focus in computer vision. In the context of industrial image inspection, conventional semantic segmentation models fail to maintain the segmentation consistency of fixed components across varying contextual environments due to a lack of perception of object contours. Given the real-time constraints and limited computing capability of industrial ...

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs

Recent advances in Large Reasoning Models (LRMs) have shown impressive capabilities in mathematical and logical reasoning. However, current LRMs rarely admit ignorance or respond with "I don't know". Instead, they often produce incorrect answers while showing undue confidence, raising concerns about their factual reliability. In this work, we identify two pathological reasoning patterns characte...

Unsupervised Port Berth Identification from Automatic Identification System Data

Port berthing sites are regions of high interest for monitoring and optimizing port operations. Data sourced from the Automatic Identification Syste...

Near-critical gene expression in embryonic boundary precision

Embryonic development relies on the formation of sharp, precise gene expression boundaries. In the fruit fly Drosophila melanogaster, boundary forma...

Unifying Segment Anything in Microscopy with Multimodal Large Language Model

Accurate segmentation of regions of interest in biomedical images holds substantial value in image analysis. Although several foundation models for ...

Evaluating LLMs' Potential to Identify Rare Patient Identifiers in Patient Health Records.

This study explores the utility of Large Language Models (LLMs) to support finding rare patient record details that could make a patient identifiable....

May 15 2025 40380594
Exploring Data Science Students' Engagement, Usage Patterns, and Perceptions of Large Language Models in Programming.

Large Language Models (LLMs) are a type of artificial intelligence (AI) that have emerged as powerful tools for a wide range of tasks, paving the way ...

May 15 2025 40380653
Evaluating Large Language Models for the Generation of Unit Tests with Equivalence Partitions and Boundary Values

The design and implementation of unit tests is a complex task many programmers neglect. This research evaluates the potential of Large Language Mode...

BoundarySeg:An Embarrassingly Simple Method To Boost Medical Image Segmentation Performance for Low Data Regimes

Obtaining large-scale medical data, annotated or unannotated, is challenging due to stringent privacy regulations and data protection policies. In a...

Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing.

Information security aims to protect confidentiality and prevent information leakage, which inherently conflicts with the goal of information sharing....

May 14 2025 40368971
NurValues: Real-World Nursing Values Evaluation for Large Language Models in Clinical Context

This work introduces the first benchmark for nursing value alignment, consisting of five core value dimensions distilled from international nursing ...

Dynamic Snake Upsampling Operater and Boundary-Skeleton Weighted Loss for Tubular Structure Segmentation

Accurate segmentation of tubular topological structures (e.g., fissures and vasculature) is critical in various fields to guarantee dependable downs...

Private LoRA Fine-tuning of Open-Source LLMs with Homomorphic Encryption

Preserving data confidentiality during the fine-tuning of open-source Large Language Models (LLMs) is crucial for sensitive applications. This work ...

DFEN: Dual Feature Equalization Network for Medical Image Segmentation

Current methods for medical image segmentation primarily focus on extracting contextual feature information from the perspective of the whole image....

Image Segmentation via Variational Model Based Tailored UNet: A Deep Variational Framework

Traditional image segmentation methods, such as variational models based on partial differential equations (PDEs), offer strong mathematical interpr...

RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterization

Pathological diagnosis is the gold standard for tumor diagnosis, and nucleus instance segmentation is a key step in digital pathology analysis and p...

Max-Min Secrecy Rate and Secrecy Energy Efficiency Optimization for RIS-Aided VLC Systems: RSMA Versus NOMA

Integrating VLC with the RIS significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to...

[Urban Ozone Driving Factors Based on Explainable Machine Learning].

Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provincial control sites, and one background site, were se...

May 8 2025 40390396
A Systematic Review of Sensor-Based Methods for Measurement of Eating Behavior.

The dynamic process of eating-including chewing, biting, swallowing, food items, eating time and rate, mass, environment, and other metrics-may charac...

May 8 2025 40431762
Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation

Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promi...

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