Artificial Intelligence Medical Compendium

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

Showing 4,631 to 4,640 of 174,202 articles

[Minimally invasive liver surgery: current trends and future perspectives].

Zhonghua wai ke za zhi [Chinese journal of surgery] Aug 20, 2025
In recent years, the continuous optimization of minimally invasive surgical instruments and equipment for liver procedures, coupled with advancements in surgeons' technical expertise and theoretical frameworks, has propelled the personalized and prec... read more 

Leveraging artificial intelligence for prediction of pulmonary hemorrhage in preterm infants.

Journal of perinatology : official journal of the California Perinatal Association Aug 20, 2025
OBJECTIVES: To identify clinical variables and indicators associated with pulmonary hemorrhage in preterm infants. read more 

[Exploration of the application of artificial intelligence assisted bleeding point recognition in laparoscopic pancreatic surgery].

Zhonghua wai ke za zhi [Chinese journal of surgery] Aug 20, 2025
To explore the clinical application value of artificial intelligence models in identifying bleeding events and hemorrhagic points during laparoscopic pancreatic surgery. This single-center retrospective cohort study collected surgical videos of 25 ... read more 

Synergistic Modulation of Microglial Polarization by Acteoside and Ferulic Acid via Dual Targeting of Nrf2 and RORĪ³t to Alleviate Depression-Associated Neuroinflammation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 20, 2025
Acteoside (ACT) and ferulic acid (FA), the principal bioactive constituents of Baihe Dihuang decoction (BDD), possess established anti-inflammatory and antidepressant properties, but their combined effect on microglial phenotype modulation remains un... read more 

Exploration of biomarkers for predicting the prognosis of patients with diffuse large B-cell lymphoma by machine-learning analysis.

BMC immunology Aug 20, 2025
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Artificial Intelligence Applications in Healthcare: A Systematic Review of Their Impact on Nursing Practice and Patient Outcomes.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing Aug 20, 2025
BACKGROUND: Artificial Intelligence is revolutionizing healthcare by addressing complex challenges and enhancing patient care. AI technologies, such as machine learning, natural language processing, and predictive analytics, offer significant potenti... read more 

SCRIPT: Predicting Single-Cell Long-Range Cis-Regulation Based on Pretrained Graph Attention Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 20, 2025
Single-cell cis-regulatory relationships (CRRs) are essential for deciphering transcriptional regulation and understanding the pathogenic mechanisms of disease-associated non-coding variants. Existing computational methods struggle to accurately pred... read more 

Evaluating forecasting models for health service demand during the COVID-19 pandemic.

Scientific reports Aug 20, 2025
We combine daily internet search data and monthly information on medical expenditures for anti-depressants to test two distinct hypotheses in eight Australian states, covering the period from 2020 to 2022. First, whether using daily search data can h... read more 
Humans Machine Learning Pandemics COVID-19 Forecasting SARS-CoV-2 Australia Health Services Needs and Demand

Network synchrony creates neural filters promoting quiescence in Drosophila.

Nature Aug 20, 2025
Animals require undisturbed periods of rest during which they undergo recuperative processes. However, it is unclear how brain states arise that are able to dissociate an animal from its external world, enabling quiescent behaviours, while retaining ... read more 

[Preoperative discrimination of colorectal mucinous adenocarcinoma using enhanced CT-based radiomics and deep learning fusion model].

Zhonghua wai ke za zhi [Chinese journal of surgery] Aug 20, 2025
To develop a preoperative differentiation model for colorectal mucinous adenocarcinoma and non-mucinous adenocarcinoma using a combination of contrast-enhanced CT radiomics and deep learning methods. This is a retrospective case series study. Clini... read more 
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