Artificial Intelligence Medical Compendium

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

Showing 21,411 to 21,420 of 216,348 articles

ELOVL1 promotes the progression of intrahepatic cholangiocarcinoma by enhancing endoplasmic reticulum stress and the PI3K/AKT/mTOR signaling pathway.

Biology direct
BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy characterized by an adverse outcome attributed to delayed detection, elevated recurrence rates, and resistance to chemotherapy. Identifying innovative indicato... read more 

Artificial intelligence predicts sex-specific risk of metabolic dysfunction-associated steatotic liver disease.

Biology of sex differences
BACKGROUND & AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) exhibits well-established sex differences across its risk factors, disease progression, and liver-related and extrahepatic outcomes. We trained sex-specific machine l... read more 

Feasibility and Reproducibility of a Structure-Guided Deep Learning Model for Automatic Detection of the Standard Sagittal Plane in First-Trimester Nuchal Translucency Assessment Using 3D Ultrasound.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Accurate nuchal translucency (NT) measurement for assessing the risk of fetal genetic abnormalities requires precise acquisition of the mid-sagittal plane (MSP). However, achieving an appropriate MSP is technically challenging due to anat... read more 

Physics-Guided Neural Network for Quantitative Parameter Mapping Using Balanced Steady State Free Precession MRI.

Magnetic resonance in medicine
PURPOSE: To propose a new method using a physics-guided neural network for quantitative parameter mapping in balanced steady-state free precession (bSSFP) imaging. THEORY AND METHODS: We trained physics-guided neural networks with a multilayer percep... read more 

Multimodal Nomogram for the Prenatal Risk Assessment of Hypoplastic Left Heart Syndrome Using Self-Supervised Learning.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: This retrospective study aims to develop and validate a multimodal nomogram for the prenatal risk assessment of hypoplastic left heart syndrome (HLHS) and to explore significant risk factors for HLHS. METHODS: This retrospective study enr... read more 

Will the advancement of GAI diminish international students' reliance on Chinese language teachers? Evidence from SEM and FsQCA.

Acta psychologica
With the rapid advancement of generative artificial intelligence (GAI), the traditional teacher-student relationship in international Chinese language education is undergoing substantial transformation. This study investigates whether and how GAI res... read more 

Artificial intelligence, omics, and biomarkers: Redefining lung cancer early detection.

Current problems in cancer
Lung cancer, the leading cause of death worldwide, claims millions of lives yearly, largely due to limited early interventions. Currently used lung cancer screening methods are still limited in their reach and accuracy due to invasiveness, radiation ... read more 

Surgical technology update for ophthalmic surgery: heads-up display, artificial intelligence, instrumentation, and robotics.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Rapid advances in surgical visualization, microsurgical instrumentation, artificial intelligence (AI), and robotic assistance are reshaping ophthalmic surgery. This review evaluates current clinical and experimental evidence to det... read more 

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Cell
Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-scale biomarker discovery. Here, we present "Path2Space," a deep-learning model that predicts spatial... read more