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Prevention of medical errors

Latest AI and machine learning research in prevention of medical errors for healthcare professionals.

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Showing 1450-1470 of 5,107 articles
Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios

Mammographic screening is an effective method for detecting breast cancer, facilitating early diag...

Closed-Form Feedback-Free Learning with Forward Projection

State-of-the-art methods for backpropagation-free learning employ local error feedback to direct i...

Vision-Aided Channel Prediction Based on Image Segmentation at Street Intersection Scenarios

Intelligent vehicular communication with vehicle road collaboration capability is a key technology...

Vision Aided Channel Prediction for Vehicular Communications: A Case Study of Received Power Prediction Using RGB Images

The communication scenarios and channel characteristics of 6G will be more complex and difficult t...

Towards Communication-Efficient Adversarial Federated Learning for Robust Edge Intelligence

Federated learning (FL) has gained significant attention for enabling decentralized training on ed...

Detecting Unauthorized Drones with Cell-Free Integrated Sensing and Communication

Integrated sensing and communication (ISAC) boosts network efficiency by using existing resources ...

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents

Recent large language models (LLMs) have demonstrated significant advancements, particularly in th...

Scene Understanding Enabled Semantic Communication with Open Channel Coding

As communication systems transition from symbol transmission to conveying meaningful information, ...

Benchmarking Generative AI for Scoring Medical Student Interviews in Objective Structured Clinical Examinations (OSCEs)

Objective Structured Clinical Examinations (OSCEs) are widely used to assess medical students' com...

Communication-Efficient Federated Learning Based on Explanation-Guided Pruning for Remote Sensing Image Classification

Federated learning (FL) is a decentralized machine learning paradigm in which multiple clients col...

Secure Semantic Communication With Homomorphic Encryption

In recent years, Semantic Communication (SemCom), which aims to achieve efficient and reliable tra...

Optimizing Secure Quantum Information Transmission in Entanglement-Assisted Quantum Networks

Quantum security improves cryptographic protocols by applying quantum mechanics principles, assuri...

AI-based Identity Fraud Detection: A Systematic Review

With the rapid development of digital services, a large volume of personally identifiable informat...

Leveraging artificial intelligence-mediated communication for cancer prevention and control and drug addiction: A systematic review.

OBJECTIVE: To conduct a systematic review on Artificial Intelligence-Mediated Communication (AIMC) b...

Jan 2025 40036982
WhiSPA: Semantically and Psychologically Aligned Whisper with Self-Supervised Contrastive and Student-Teacher Learning

Current speech encoding pipelines often rely on an additional text-based LM to get robust represen...

Scientific Map of Artificial Intelligence in Communication (2004-2024)

Introduction: Artificial Intelligence (AI) is having a significant impact in the field of communic...

Towards Dynamic Neural Communication and Speech Neuroprosthesis Based on Viseme Decoding

Decoding text, speech, or images from human neural signals holds promising potential both as neuro...

Integrating Explainable AI for Effective Malware Detection in Encrypted Network Traffic

Encrypted network communication ensures confidentiality, integrity, and privacy between endpoints....

Collaborative Inference Acceleration with Non-Penetrative Tensor Partitioning

The inference of large-sized images on Internet of Things (IoT) devices is commonly hindered by li...

Resource Allocation for the Training of Image Semantic Communication Networks

Semantic communication is a new paradigm that aims at providing more efficient communication for t...

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