Military Medicine

AI-Assisted Decision-Making in Long-Term Care: Qualitative Study on Prerequisites for Responsible Innovation.

BACKGROUND: Although the use of artificial intelligence (AI)-based technologies, such as AI-based decision support systems (AI-DSSs), can help sustain and improve the quality and efficiency of care, their deployment creates ethical and social challenges. In recent years, a growing prevalence of high-level guidelines and frameworks for responsible AI innovation has been observed. However, few studi...

An Innovative Device Based on Human-Machine Interface (HMI) for Powered Wheelchair Control for Neurodegenerative Disease: A Proof-of-Concept.

In the global context, advancements in technology and science have rendered virtual, augmented, and mixed-reality technologies capable of transforming clinical care and medical environments by offering enhanced features and improved healthcare services. This paper aims to present a mixed reality-based system to control a robotic wheelchair for people with limited mobility. The test group comprised...

Ethical Challenges and Opportunities in Applying Artificial Intelligence to Cardiovascular Medicine.

Much anticipation surrounds artificial intelligence's (AI) emergence as a promising tool in health care. It offers potential to revolutionise clinical...

Shaping the future of healthcare in British Columbia: Establishing provincial clinical governance for responsible deployment of artificial intelligence tools.

As healthcare embraces the transformative potential of Artificial Intelligence (AI), it is imperative to safeguard patient and provider safety, equity...

Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care phys...

Speech-based recognition and estimating severity of PTSD using machine learning.

BACKGROUND: Traditional methodologies for diagnosing post-traumatic stress disorder (PTSD) primarily rely on interviews, incurring considerable costs ...

Optimized efficient attention-based network for facial expressions analysis in neurological health care.

Facial Expression Analysis (FEA) plays a vital role in diagnosing and treating early-stage neurological disorders (NDs) like Alzheimer's and Parkinson...

Prospective Randomized Study on the Use of Robot-Assisted Postoperative Visits.

Robot-assisted visits, as part of telemedicine, can offer doctors the opportunity to take care of patients. Due to the COVID-19 pandemic, there has b...

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future.

The rapid advancement of artificial intelligence (AI) in healthcare has revolutionized the industry, offering significant improvements in diagnostic a...

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 enhanced accuracy and efficiency in detecting variou...

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 to wars, terrorism, and pandemic disease situations...

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' capacity to analyse medical images, thereby impro...

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 vision loss globally. A prompt and accurate diagnosis...

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) fiber optics technology assists telemedicine appl...

Enhancing post-traumatic stress disorder patient assessment: leveraging natural language processing for research of domain criteria identification using electronic medical records.

BACKGROUND: Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial ...

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, is crucial for treating with targeted therapies; ...

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 fatalities globally, thereby emerging as one of t...

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 tissue, subsequently able to progress to cirrhosis or ...

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 potential diagnostic biomarker for PTSD is investigat...

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 larger use of sensors for remote care and artificial i...