Public Health & Policy

Military Medicine

Latest AI and machine learning research in military medicine for healthcare professionals.

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Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine.

Large Language Models (LLMs) are a key component of generative artificial intelligence (AI) applicat...

Ethics Principles for Artificial Intelligence-Based Telemedicine for Public Health.

The use of artificial intelligence (AI) in the field of telemedicine has grown exponentially over th...

Securing Multimedia Using a Deep Learning Based Chaotic Logistic Map.

Telemedicine and online consultations with doctors has become very popular during the pandemic and i...

Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction.

Nutrition is a cross-cutting sector in medicine, with a huge impact on health, from cardiovascular d...

Multi-path decoder U-Net: A weakly trained real-time segmentation network for object detection and localization in ultrasound scans.

Detecting and localizing an anatomical structure of interest within the field of view of an ultrasou...

A practical guide to the development and deployment of deep learning models for the orthopedic surgeon: part II.

Deep learning has the potential to be one of the most transformative technologies to impact orthoped...

Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the informati...

Artificial intelligence in medicine - is too much transparency a good thing?

Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Comp...

AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.

Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep learni...

Digital health-high tech or high touch?

Digital transformation in medicine refers to the implementation of information technology-driven dev...

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increa...

Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem.

Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a d...

Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. A...

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC.

The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in artificial i...

Emulate randomized clinical trials using heterogeneous treatment effect estimation for personalized treatments: Methodology review and benchmark.

Big data and (deep) machine learning have been ambitious tools in digital medicine, but these tools ...

A practical guide to the development and deployment of deep learning models for the Orthopedic surgeon: part I.

Deep learning has a profound impact on daily life. As Orthopedics makes use of this rapid escalation...

A Dynamic Deployment Method of Security Services Based on Malicious Behavior Knowledge Base.

In view of various security requirements, there are various security services in the network. In par...

MT-GCNN: Multi-Task Learning with Gated Convolution for Multiple Transmitters Localization in Urban Scenarios.

With the advance of the Internet of things (IoT), localization is essential in varied services. In u...

Optimizing Face Recognition Inference with a Collaborative Edge-Cloud Network.

The rapid development of deep-learning-based edge artificial intelligence applications and their dat...

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