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Artificial intelligence is fundamentally changing how health content is encountered and acted upon across both the information and healthcare ecosystems. AI systems now generate claims, curate information, interpret symptoms, synthesize…
Recent breakthroughs in artificial intelligence through foundation models and agents have accelerated the evolution of computational pathology. Demonstrated performance gains reported across academia in benchmarking datasets in predictive…
Retinal imaging has emerged as a powerful, non-invasive modality for detecting and quantifying biomarkers of systemic diseases-ranging from diabetes and hypertension to Alzheimer's disease and cardiovascular disorders but current insights…
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Recent advancements in artificial intelligence (AI) have precipitated significant breakthroughs in healthcare, particularly in refining diagnostic procedures. However, previous studies have often been constrained to limited functionalities.…
Deep neural networks power most recent successes of artificial intelligence, spanning from self-driving cars to computer aided diagnosis in radiology and pathology. The high-stake data intensive process of surgery could highly benefit from…
In recent decades, artificial intelligence (AI) including machine learning (ML) have become vital for space missions enabling rapid data processing, advanced pattern recognition, and enhanced insight extraction. These tools are especially…
The main goal from this study is to discuss the main features of Artificial intelligence (AI) as well as their applicability for early cardiovascular Disease (CVDs) Detection, Material and Method : Systematic review approach Results : It…
AI is a magnificent field that directly and profoundly touches on numerous disciplines ranging from philosophy, computer science, engineering, mathematics, decision and data science and economics, to cognitive science, neuroscience and…
Healthcare data is increasing in size at an unprecedented speed with much attention on big data analysis and Artificial Intelligence application for quality assurance, clinical training, severity triaging, and decision support. Radiology is…
The implementation of Artificial Intelligence (AI) in the healthcare industry has garnered considerable attention, attributable to its prospective enhancement of clinical outcomes, expansion of access to superior healthcare, cost reduction,…
As the volume and complexity of nonclinical toxicology studies continue to increase, toxicologic pathology reporting faces persistent challenges, including fragmented sources of data (e.g., histopathology images, clinical pathology and…
Recent technological advances in healthcare have led to unprecedented growth in patient data quantity and diversity. While artificial intelligence (AI) models have shown promising results in analyzing individual data modalities, there is…
Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related…
Designing Artificial Intelligence (AI) solutions that can operate in real-world situations is a highly complex task. Deploying such solutions in the medical domain is even more challenging. The promise of using AI to improve patient care…
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep…
Recent significant increases in affordable and accessible computational power and data storage have enabled machine learning to provide almost unbelievable classification and prediction performances compared to well-trained humans. There…
Neuroscience and neurotechnology are currently being revolutionized by artificial intelligence (AI) and machine learning. AI is widely used to study and interpret neural signals (analytical applications), assist people with disabilities…