Military Medicine

[The innovation and challenge of artificial intelligence in the whole process management of fundus disease].

Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases, yet it faces challenges in clinical translation, data quality, algorithm interpretability, and cross-cultural adaptability. AI has proven effective in the efficient screening, accurate diagnosis, personalized treatment recommendations, and prognosi...

Position Statements of the Emerging Trends Committee of the Asian Oceanian Society of Radiology on the Adoption and Implementation of Artificial Intelligence for Radiology.

Artificial intelligence (AI) is rapidly gaining recognition in the radiology domain as a greater number of radiologists are becoming AI-literate. However, the adoption and implementation of AI solutions in clinical settings have been slow, with points of contention. A group of AI users comprising mainly clinical radiologists across various Asian countries, including India, Japan, Malaysia, Singapo...

Enhancing Model Generalizability In Parkinson's Disease Automatic Assessment: A Semi-Supervised Approach Across Independent Experiments.

Machine learning in Parkinson's disease assessment uses data from clinically-coded movements, such as finger tapping, to objectively measure motor imp...

Video-based Clinical Gait Analysis in Parkinson's Disease: A Novel Approach Using Frontal Plane Videos and Machine Learning.

Gait can be significantly impaired by neurological conditions such as Parkinson's disease (PD). Gait impairments can be quantified by using instrument...

Smartphone-Based Balance Assessment Using Machine Learning.

This study explores the potential of smartphones to objectively assess balance, which is crucial for the elderly and individuals recovering from vario...

Remote Motor Rehabilitation: EMG-IMU based Deep Learning Model Improves the Estimate of Wrist Kinematics.

Technology for motor rehabilitation faces challenges in uncontrolled settings, such as at home. In these real-world scenarios, robust signals like ele...

Personalised Speech-Based PTSD Prediction Using Weighted-Instance Learning.

Post-traumatic stress disorder (PTSD) is a prevalent disorder that can develop in people who have experienced very stressful, shocking, or distressing...

Acute Stress Disorder Detection using Machine Learning based on resting-state fMRI.

Early diagnosis of Acute Stress Disorder (ASD) is important, given its potential progression to post-traumatic system disorder (PTSD). The current dia...

T-MAC: CPU Renaissance via Table Lookup for Low-Bit LLM Deployment on Edge

The deployment of Large Language Models (LLMs) on edge devices is increasingly important to enhance on-device intelligence. Weight quantization is c...

Benchmarking Deep Learning Models on NVIDIA Jetson Nano for Real-Time Systems: An Empirical Investigation

The proliferation of complex deep learning (DL) models has revolutionized various applications, including computer vision-based solutions, prompting...

A Comprehensive Survey of Foundation Models in Medicine

Foundation models (FMs) are large-scale deep learning models trained on massive datasets, often using self-supervised learning techniques. These mod...

Participatory Approaches in AI Development and Governance: Case Studies

This paper forms the second of a two-part series on the value of a participatory approach to AI development and deployment. The first paper had craf...

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom ...

[An overview of investments in the development of the Russian Medtech market and the prospects for the impact of digitalization in medicine on the economic performance of companies until 2030].

Today, the topic of digitalization, the introduction of innovations based on Big Data, the complexity of technologies due to the introduction of artif...

A Health Care Clinical Data Platform for Rapid Deployment of Artificial Intelligence and Machine Learning Algorithms for Cancer Care and Oncology Clinical Trials.

The xCures platform aggregates, organizes, structures, and normalizes clinical EMR data across care sites, utilizing advanced technologies for near re...

[The ethics of IA in medicine must be based on the practical ethics of the healthcare relationship].

THE ETHICS OF IA IN MEDICINE MUST BE BASED ON THE PRACTICAL ETHICS OF THE HEALTHCARE RELATIONSHIP. Artificial intelligence (AI) offers more and more a...

Current Scenario and Future Prospects of Adverse Drug Reactions (ADRs) Monitoring and Reporting Mechanisms in the Rural Areas of India.

Pharmacovigilance (PV) deals with the detection, collection, assessment, understanding, and prevention of adverse effects associated with drugs. The o...

[Not Available].

With the emergence of innovations and technological advancements – exemplified by telemedicine and more recently by the extremely rapid developm...

Advances and opportunities in the new digital era of telemedicine, e-health, artificial intelligence, and beyond.

Maintaining High-Touch in High-Tech Digital Health Monitoring and Multi-Omics Prognostication: Ethical, Equity, and Societal Considerations in Precision Health for Palliative Care.

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (AI) continue to revolutionize health care, usherin...