Military Medicine

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the screening burden on ophthalmologists and neonatologists and improve the detection of treatment-requiring ROP. Neural networks such as convolutional neural ...

Generative Adversarial Networks in Medicine: Important Considerations for this Emerging Innovation in Artificial Intelligence.

The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity for framework regulations to ensure equitable and safe deployment of technology. Generative Ad...

Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus.

PURPOSE OF REVIEW: The application of artificial intelligence (AI) technologies in screening and diagnosing retinal diseases may play an important rol...

Utility of ChatGPT in Clinical Practice.

ChatGPT is receiving increasing attention and has a variety of application scenarios in clinical practice. In clinical decision support, ChatGPT has b...

Simulator, machine learning, and artificial intelligence: Time has come to assist prenatal ultrasound diagnosis.

In this Commentary authors investigated and extended the role of simulator in assisting obstetric sonographers in training program. The interconnectio...

Digital Education for the Deployment of Artificial Intelligence in Health Care.

Artificial Intelligence (AI) represents a significant milestone in health care's digital transformation. However, traditional health care education an...

Smart Chemical Sensor and Biosensor Networks for Healthcare 4.0.

Driven by technological advances from Industry 4.0, Healthcare 4.0 synthesizes medical sensors, artificial intelligence (AI), big data, the Internet o...

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

BACKGROUND: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, propos...

Health system-scale language models are all-purpose prediction engines.

Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by for...

From SLAM to Situational Awareness: Challenges and Survey.

The capability of a mobile robot to efficiently and safely perform complex missions is limited by its knowledge of the environment, namely the . Advan...

Letter to the Editor - Update from Ukraine: Development of the Cloud-based Platform for Patient-centered Telerehabilitation of Oncology Patients with Mathematical-related Modeling.

This Letter to the Editor provides an update on the research from the Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine...

Deployment of an electrocorticography system with a soft robotic actuator.

Electrocorticography (ECoG) is a minimally invasive approach frequently used clinically to map epileptogenic regions of the brain and facilitate lesio...

Show Your Work: Responsible Model Reporting in Health Care Artificial Intelligence.

Standardized and thorough model reporting is an integral component in the development and deployment of machine learning models in health care. Model ...

More Process, Less Principles: The Ethics of Deploying AI and Robotics in Medicine.

Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical th...

Critical Appraisal of Artificial Intelligence-Enabled Imaging Tools Using the Levels of Evidence System.

Clinical adoption of an artificial intelligence-enabled imaging tool requires critical appraisal of its life cycle from development to implementation ...

Applications of artificial intelligence-machine learning for detection of stress: a critical overview.

Psychological distress is a major contributor to human physiology and pathophysiology, and it has been linked to several conditions, such as auto-immu...

A "Do No Harm" Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence-Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework.

Given the impact artificial intelligence (AI)-based medical technologies (hardware devices, software programs, and mobile apps) can have on society, d...

Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch.

Mobile health (mHealth) utilizes mobile devices, mobile communication techniques, and the Internet of Things (IoT) to improve not only traditional tel...

Centering Patients' Voices in Artificial Intelligence‒Based Telemedicine.

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 the past decade, along with the adoption of AI-based...