Latest Articles for Healthcare Technology

A study shows the benefits of a new application in rehabilitation remote monitoring.

A method to secure neural networks against vulnerabilities in memory.

DDPET-3D enhances low-dose PET images for better diagnosis.

Using advanced sensors during training helps robots perform tasks better.

This method identifies anomalies in images using limited samples.

LoRA-Ensemble combines models for better predictions and uncertainty management.

A new method improves understanding of Graph Neural Networks' predictions.

New methods improve decision-making in constrained reinforcement learning.

A dataset that simplifies querying Electronic Health Records through natural language.

Examining issues that skew reported machine learning performance metrics.

The study investigates balance measurement tools for stroke recovery.

Cluster ComBat improves medical data analysis by reducing bias efficiently.

AI tools improve glaucoma referrals and patient outcomes.

A new framework improves diagnosis of brain disorders through enhanced EEG analysis.

New model improves disease classification using limited labeled and unlabeled medical images.

This article discusses TULIP, a method for better uncertainty estimation in machine learning.

KG-FIT combines knowledge graphs with language model insights for richer data representation.

Learn how AltGDmin addresses missing data in a federated setting.

Integrating IoMT and fog computing improves real-time healthcare data management.

A new method to improve federated learning through Multi-Level Additive Modeling.

This explores how probabilistic approaches improve contrastive learning in machine learning.

Understanding how persona shapes interactions with conversational agents in various fields.

This research focuses on using AI for early detection of retinal diseases.

A new method improves fairness in federated learning across diverse communities.

A new framework improves machine learning from diverse information sources.

A new algorithm enhances prediction sets for better expert decision-making.

Introducing an effective tree-based method for multi-label classification that addresses uncertainty.

New technique improves 3D pose estimation accuracy despite missing data.

A new loss function improves synthetic tabular data using GANs for medical research.

TGDP improves data generation in scenarios with scarce training examples.

Examining smaller AI models' effectiveness and cost compared to larger counterparts.

SGDIR simplifies image registration for better diagnostic accuracy and efficiency.

New method reduces hallucination in language models that process images and text.

AI method enhances radiotherapy dose predictions by estimating uncertainty.

Exploring how inter-concept relationships can enhance AI system transparency.

TSRMs offer a new way to analyze time series data effectively.

The BraTS Challenge pushes boundaries in automated meningioma segmentation using deep learning.

A new benchmark for evaluating fairness in representation learning methods.

Understanding and mitigating hallucination in AI for reliable performance.

A novel approach improves merging of AI models for better performance and efficiency.