Latest Articles for Healthcare Technology

This research focuses on improving brain tumor segmentation with a new model approach.

The CIEL Library enhances access to clinical trial data for cancer treatment.

Introducing S3, a method to enhance time-series data analysis through intelligent rearrangement.

A new model aids in analyzing COVID-19 medical imaging.

A new method called ADEPT improves offline reinforcement learning through adaptive models.

A new approach improves model performance with different data sources.

A new method for fine-tuning language models using self-attention.

New method enhances reliability of predictions by addressing uncertainty in machine learning.

A new AI tool improves the review process for chest X-ray reports.

Using vector embeddings to improve AI tools in low-resource healthcare settings.

A deep dive into how uncertainty affects neural network predictions.

MediQ redefines medical AI conversations for improved patient outcomes.

Robust reinforcement learning adapts strategies for reliable outcomes despite real-world challenges.

LinkLogic provides clarity and reliability for link prediction in knowledge graphs.

Understanding AI decision-making is crucial for trust and ethical use.

VERT improves ultrasound imaging in complex areas, enhancing clarity and accuracy.

A new framework improves action recognition in unseen movements through enhanced semantic understanding.

A practical method to improve fairness in algorithms without sacrificing accuracy.

A new framework enhances synthetic data creation while protecting personal information.

Examining how machine learning affects human choices and outcomes.

Introducing PrivacyRestore to protect user data while using large language models.

GNAN combines interpretability and accuracy for graph-based AI models.

This article discusses role-playing and personalization in language models.

This study explores advanced methods for efficient data labeling using neural network techniques.

Introducing CUT, a framework for realistic and diverse anomaly generation without extra training.

This study assesses how aiChat compares to medical librarians in answering clinical questions.

A new method enhances uncertainty estimation in machine learning predictions.

Cardiovascular digital twins help tailor treatments by analyzing individual patient data.

A new framework enhances prediction accuracy and data privacy in federated learning.

A framework to measure and improve uncertainty in image generation models.

HOGE enhances explanations of Graph Neural Networks using cell complexes.

CVQBM offers novel methods for data generation and analysis using quantum technology.

Research explores new methods for breast imaging without traditional contrast agents.

Advances in automatic lymph node segmentation enhance cancer treatment accuracy.

Mamba models improve accuracy and efficiency in interpreting medical images.

WGBoost offers advanced probabilistic predictions and better uncertainty handling in various fields.

An advanced method for frequency estimation while safeguarding data privacy.

A new framework aims to improve accuracy and efficiency in medical image analysis.

Research explores advanced loss functions for improving GAN performance using Genetic Programming.

A method to assess the reliability of AI outputs in healthcare and beyond.