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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 379-399 of 3,901 articles
Zero-shot 3D anomaly detection via online voter mechanism.

3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by l...

Simulation of a Free Boundary Cell Migration Model through Physics Informed Neural Networks.

Understanding the complexities of single-cell migration is facilitated by computational modeling, wh...

Foundation models in pathology: bridging AI innovation and clinical practice.

Foundation models are revolutionising pathology by leveraging large-scale, pretrained artificial int...

Development and Validation of a Scale for Nurses' Ethical Awareness in The Use of Artificial Intelligence: A Methodological Study.

The integration of artificial intelligence in nursing practice presents significant ethical challeng...

Boosting polyp screening with improved point-teacher weakly semi-supervised.

Polyps, like a silent time bomb in the gut, are always lurking and can explode into deadly colorecta...

Boundary-Enhanced $U^{2}$-Net for Simultaneous Four-Chamber Segmentation in Transthoracic Echocardiography.

The heart, responsible for circulating blood throughout our body, contains four chambers. Existing a...

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 powerfu...

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 reco...

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

Information security aims to protect confidentiality and prevent information leakage, which inherent...

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 rat...

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

Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provinci...

Generative Artificial Intelligence Biases, Limitations and Risks in Nuclear Medicine: An Argument for Appropriate Use Framework and Recommendations.

Generative artificial intelligence (AI) algorithms for both text-to-text and text-to-image applicati...

DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation.

Medical image segmentation plays a crucial role in computer-aided diagnosis. By segmenting pathologi...

HCAP: Hybrid cyber attack prediction model for securing healthcare applications.

The rapid development and integration of interconnected healthcare devices and communication network...

Enhancing Privacy-Preserving Cancer Classification with Convolutional Neural Networks.

Precision medicine significantly enhances patients prognosis, offering personalized treatments. Part...

A Comparative Analysis of Federated and Centralized Learning for SpO2 Prediction in Five Critical Care Databases.

This study explores the potential of federated learning (FL) to develop a predictive model of hypoxe...

Secure Extraction of Personal Information from EHR by Federated Machine Learning.

Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs)...

Precise Identification of Oral Cancer Lesions Using Artificial Intelligence.

Dentists, especially those who are not oral lesion specialists and live in rural areas, need an arti...

Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.

Community-based palliative care is a useful, but underutilized service to support seriously ill olde...

Advancing Chest X-ray Diagnostics via Multi-Modal Neural Networks with Attention.

The healthcare field is undergoing a profound shift, with deep learning in AI increasingly augmentin...

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