Artificial Intelligence Medical Compendium

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

Showing 61,671 to 61,680 of 229,091 articles

Artificial intelligence based prediction of first recurrence in neovascular age related macular degeneration with validation by 19 experts.

Scientific reports Jan 16, 2026
This study aimed to investigate the value and difference in predictive performance between ophthalmologists and a previously developed and validated artificial intelligence (AI) model, and to evaluate how AI assistance influences expert decision-maki... read more 

Plasma glutamic acid predicts myelosuppression and mortality in septic patients using machine learning.

Scientific reports Jan 16, 2026
Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morbidity and mortality. Recent evidence suggests that amino acid metabolism, particularly that of glutamic acid, may influence hematopoietic function and... read more 

Classifying retinal images via vascular-optic disc cross-segmentation and attentive feature selection.

Scientific reports Jan 16, 2026
The prevalence of retinal disorders is rising at an alarming rate, posing a significant risk of irreversible blindness without timely intervention. Recent advancements in artificial intelligence (AI) have enabled the development of automated screenin... read more 

DrugBank mining with machine learning reveals novel candidates for BCL-2 inhibition.

Scientific reports Jan 16, 2026
Apoptosis, also known as programmed cell death, is a fundamental biological process essential for development and cellular homeostasis. An imbalance in the levels of pro- and antiapoptotic proteins of the BCL-2 family can inhibit apoptosis and contri... read more 

AI-assisted multimodal assessment for right ventricular function from echocardiography predicts mortality in patients with pulmonary hypertension and right heart failure.

Scientific reports Jan 16, 2026
Right ventricular (RV) strain is an important factor in evaluating RV function. This study aimed to predict mortality in patients with pulmonary hypertension (PH) and right heart failure (RHF) using an artificial intelligence (AI)-assisted multimodal... read more 

An attention-augmented multimodal classification of alzheimer's disease and parkinson's disease vs healthy controls using MRI, EEG, and SNP data.

Scientific reports Jan 16, 2026
Due to the late manifestation of structural symptoms and symptomatic overlap, neurodegenerative diseases such as Parkinson's Disease (PD) and Alzheimer's Disease (AD) remain difficult to diagnose accurately. In order to categorize AD and PD in compar... read more 

The peak shifting electricity consumption management and influencing factors of smart grid from recurrent neural network model and deep learning.

Scientific reports Jan 16, 2026
This study uses Recurrent Neural Network (RNN) model and Electricity Consumption (EC) management model to conduct in-depth research and analysis to achieve effective management of peak shifting EC in smart grids and analyze its influencing factors. A... read more 

Visual perception based deep learning transformers for classifying paintings and photographs through feature extraction.

Scientific reports Jan 16, 2026
The application of computer vision techniques that have been used in various domains and artwork is not an exception. The latest models of deep learning are applied for processing and classification of digital images to analyze textures, color compos... read more 

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

NPJ digital medicine Jan 16, 2026
The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic dysfunction-associated steatohepatitis (MASH) is a critical link leading to cirrhosis and hepatocellular carcinoma. Yet the responsible cellular progra... read more 

DynaGraph: interpretable dynamic graph learning for temporal electronic health records.

NPJ digital medicine Jan 16, 2026
Electronic health records (EHRs) capture evolving physiological processes, yet most machine learning models impose static or sequential assumptions that flatten their temporal and relational complexity. We introduce DynaGraph, a dynamic and interpret... read more 
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