AIMC Topic: Artificial Intelligence

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Artificial Intelligence Chatbots in Healthcare: Navigating Accuracy, Privacy, and Global Applicability.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association

Machine learning application in otology.

Auris, nasus, larynx
This review presents a comprehensive history of Artificial Intelligence (AI) in the context of the revolutionary application of machine learning (ML) to medical research and clinical utilization, particularly for the benefit of researchers interested...

A Deep Auto-Optimized Collaborative Learning (DACL) model for disease prognosis using AI-IoMT systems.

Scientific reports
In modern healthcare, integrating Artificial Intelligence (AI) and Internet of Medical Things (IoMT) is highly beneficial and has made it possible to effectively control disease using networks of interconnected sensors worn by individuals. The purpos...

Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models.

Journal of nursing care quality
BACKGROUND: With the rapidly advancing technological landscape of health care, evaluating the potential use of artificial intelligence (AI) models to prepare nursing care plans is of great importance.

Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

Journal of neurosurgery
OBJECTIVE: It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly ...

Evaluation of aesthetic outcomes of mandibular reconstruction using artificial intelligence.

Head & neck
BACKGROUND: Although vascularized bone graft (VBG) transfer is the current standard for mandibular reconstruction, reconstruction with a mandibular reconstruction plate (MRP) and with a soft-tissue flap (STF) alone remain crucial options for patients...

Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (IgG4-ROD) and orbital MALT lymphoma using artificial intelligence (AI) and hematoxylin-eosin (HE) images.