Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,961 to 1,970 of 235,116 articles

Xerogenic medications and clinical markers of salivary hypofunction.

Clinical oral investigations
OBJECTIVES: To determine whether xerogenic medication-class exposure and chair-side salivary markers contribute to risk stratification of objective salivary hypofunction across a broad clinical age spectrum, using conventional regression and explaina... read more 

Stability and Thermophysical Properties of Silicon Carbide and Carbon Nanofibers Thermal Oil Hybrid Nanofluids.

Discover nano
Hybrid Nanofluids (HNFs) have been widely investigated to improve the thermal efficiency of energy systems, thereby reducing overall energy consumption. Silicon Carbide (SiC) nanoparticles offer excellent thermal stability, and Carbon Nanofibers (CNF... read more 

Complementary Error Profiles of Human Readers and Large Language Models in Detecting AI-Generated Chest Radiographs: A Comparative Reader Study.

Journal of imaging informatics in medicine
Frontier large language models (LLMs) and diffusion models can generate realistic chest radiographs, raising concerns for dataset integrity when provenance metadata are absent. We compared authenticity judgments by two radiologists, two nonradiologis... read more 

From the operating room to the cloud: the evolving continuum from live surgical broadcasting to remote tele-surgery.

Journal of robotic surgery
In the last four decades, the transmission of a live surgical operation to a remote audience has evolved from closed-circuit educational broadcast into a fully remote, robot-assisted surgery performed across different continents. This review maps tha... read more 

Perspectives of robotic surgeons on the strengths, weaknesses, opportunities, and threats of robotic surgery in india: a cross-sectional survey.

Journal of robotic surgery
Robotic surgery is increasingly being adopted in India, but its wider implementation is associated with economic, training, and resource-related challenges. This study assessed the perspectives of surgeons performing robotic surgery in India regardin... read more 

Artificial intelligence-based prediction of cerebrospinal fluid leak in skull base surgery: a scoping review.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: Cerebrospinal fluid (CSF) leak remains one of the most significant complications of skull base surgery, particularly in endoscopic endonasal and transsphenoidal approaches. Accurate risk stratification may improve surgical planning and re... read more 

GMUPC: a new package for global-minimum search of large uranyl peroxide clusters with machine learning potentials and DFT calculations.

Journal of molecular modeling
CONTEXT: This study presents the development of the GMUPC package, which integrates machine learning potentials (MLPs) to efficiently and accurately identify the possible structures of fullerene-like uranyl peroxide Un clusters spanning a broad size ... read more 

Optimizing AI-assisted decision-making in mammography screening: focusing on uncertainties.

Insights into imaging
OBJECTIVE: To evaluate an AI-based decision-support system for mammography interpretation, assessing its impact on diagnostic performance. MATERIALS AND METHODS: This retrospective study analyzed 130,838 mammograms from 35,709 patients with confirmed... read more 

Video-based analysis of camera-instrument distance dynamics and operative efficiency in expert and novice robot-assisted partial nephrectomy.

Journal of robotic surgery
In robot-assisted partial nephrectomy (RAPN), experts and novices differ in many metrics, but it is unknown which difference relates to novice operative efficiency and whether it improves with early experience. We addressed these questions using rout... read more 

Impact of deep learning image reconstruction on CT radiomics reproducibility in patients with pulmonary nodules.

Insights into imaging
OBJECTIVE: Ensuring CT feature reproducibility across imaging protocols and reconstruction algorithms is essential for the generalizability of radiomics applications. This study aimed to evaluate the reproducibility of CT radiomic features in pulmona... read more