Latest AI and machine learning research in military medicine for healthcare professionals.
Accurate forecasting of financial time series increasingly relies on alternative data such as environmental, social and governance (ESG) scores and news-based sentiment, yet the way these signals interact and when they actually improve forecasts is still poorly understood. We introduce an interpretable hybrid framework for asset return forecasting that combines a Temporal Fusion Transformer (TFT) ...
Knee injuries are one of the most common complaints in sports medicine. Magnetic resonance imaging is an essential adjunct to clinical evaluation for many traumatic injuries and overuse conditions. Given the heavy use of knee magnetic resonance imaging, developing faster magnetic resonance imaging acquisition methods and deployment in clinical practice would be valuable. In this article, we illust...
BACKGROUND: Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patte...
Wearable ultrasound sensing systems are rapidly emerging for precise, continuous, and intuitive biomedical monitoring and human-in-the-loop interactio...
Sepsis prediction models trained on ICU data often fail to generalize under external validation because of distribution shift. Prior studies have focu...
Foundation models in artificial intelligence are revolutionizing healthcare by utilizing large-scale unlabelled data for pretraining. However, their i...
BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorrhagic stroke and ischemic stroke require completel...
Predicting workplace conflicts before they escalate into formal disputes or collective action represents a persistent challenge in organizational mana...
Artificial Intelligence (AI) is revolutionizing reproductive medicine by enhancing fertility treatments, childbirth monitoring, and postnatal care. AI...
Achieving clinical level performance and widespread deployment for generating radiology impressions encounters a giant challenge for conventional arti...
The introduction of foundational models, specifically large language models, has promised a health care transformation. However, the field is rapidly ...
Applications of data science and artificial intelligence (AI) in global health are expanding, yet research remains fragmented and often misaligned wit...
Accurate blood glucose level (BGL) forecasting is critical for diabetes self-management and clinical decision-making. Although deep learning models ba...
Episodic memory integrates what, where, and when of experience into a coherent autobiographical narrative. Decades of research have identified hippoca...
INTRODUCTION: Although personality functioning has a long psychodynamic tradition and has received renewed interest in psychotherapy research with the...
Interpretable, automated Artificial Intelligence (AI) solutions are essential for accurate 12-lead electrocardiogram (ECG) arrhythmia classification b...
A growing number of data-driven clinical decision support (CDS) tools are incorporated into tele-critical care, but the clinician perceptions of their...
Artificial intelligence (AI) is transforming patient care, but it also raises ethical questions, such as bias and transparency. While a range of well-...
Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...
BACKGROUND: Rapid integration of Large Language Models (LLMs) into oncology workflows mandates scrutiny of implicit biases that may exacerbate health ...