Public Health & Policy

Military Medicine

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

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Removing Adversarial Noise in X-ray Images via Total Variation Minimization and Patch-Based Regularization for Robust Deep Learning-based Diagnosis.

Deep learning has significantly advanced the field of radiology-based disease diagnosis, offering en...

Deep learning based diagnosis of PTSD using 3D-CNN and resting-state fMRI data.

BACKGROUND: The incidence rate of Posttraumatic stress disorder (PTSD) is currently increasing due t...

A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point of Care: The PACS-AI Platform.

The potential of artificial intelligence (AI) in medicine lies in its ability to enhance clinicians'...

Artificial Intelligence Applications in Diabetic Retinopathy: What We Have Now and What to Expect in the Future.

Diabetic retinopathy (DR) is a major complication of diabetes mellitus and is a leading cause of vis...

Fiber-optics IoT healthcare system based on deep reinforcement learning combinatorial constraint scheduling for hybrid telemedicine applications.

Telemedicine is an emerging development in the healthcare domain, where the Internet of Things (IoT)...

A deep learning-based model for detecting Leishmania amastigotes in microscopic slides: a new approach to telemedicine.

BACKGROUND: Leishmaniasis, an illness caused by protozoa, accounts for a substantial number of human...

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor,...

Artificial intelligence (AI) implementation within the National Health Service (NHS): the South West London AI Working Group experience.

In the rapidly evolving field of artificial intelligence (AI) for radiology, with a plethora of vend...

Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning.

Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tiss...

Interdisciplinary approach to identify language markers for post-traumatic stress disorder using machine learning and deep learning.

Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a pot...

Uncertainty estimation and evaluation of deformation image registration based convolutional neural networks.

Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is esse...

Liability of Health Professionals Using Sensors, Telemedicine and Artificial Intelligence for Remote Healthcare.

In the last few decades, there has been an ongoing transformation of our healthcare system with larg...

Advances in the Application of AI Robots in Critical Care: Scoping Review.

BACKGROUND: In recent epochs, the field of critical medicine has experienced significant advancement...

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies.

The quick proliferation of pandemic diseases has been imposing many concerns on the international he...

Path to autonomous soil sampling and analysis by ground-based robots.

Good site characterization is essential for the selection of remediation alternatives for impacted s...

How to mitigate the risks of deployment of artificial intelligence in medicine?

The aim of this study is to examine the risks associated with the use of artificial intelligence (AI...

Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.

BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes and may lead to irreversi...

[A look into the neighboring discipline: eHealth in oncology].

Digitalization is dramatically changing the entire healthcare system. Keywords such as artificial in...

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