Artificial Intelligence Medical Compendium

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

Showing 841 to 850 of 160,243 articles

Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques.

Scientific reports Jul 15, 2025
In the behavior of concrete, factors such as particle types, water content, aggregates, additives, and binders significantly influence its Compressive Strength (CS) properties. This study develops hybrid and ensemble models to predict compressive CS ... read more 

Structure-based machine learning screening identifies natural product candidates as potential geroprotectors.

Journal of cheminformatics Jul 15, 2025
Age-related diseases and syndromes result in poor quality of life and adverse outcomes, representing a challenge to healthcare systems worldwide. Several pharmacological interventions have been proposed to target the aging process to slow its adverse... read more 

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Scientific reports Jul 15, 2025
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an... read more 
Humans Machine Learning Prognosis Female Tumor Microenvironment Biomarkers, Tumor Male Deep Learning Gene Expression Regulation, Neoplastic Angiogenesis Inhibitors Urinary Bladder Neoplasms Neovascularization, Pathologic Angiogenesis

Leveraging satellite observations and machine learning for underwater sound speed estimation.

Communications engineering Jul 15, 2025
Underwater acoustics plays a vital role in climate science, marine ecosystems, environmental monitoring, mineral exploration, and oceanography. Accurate underwater sound speed data is crucial for acoustic modeling and applications such as sonar syste... read more 

Artificial intelligence for risk prediction in transcatheter heart valve interventions.

Expert review of cardiovascular therapy Jul 15, 2025
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Prediction of suicidal attempts among Chinese adolescents with mood disorders: a clinical study using a machine learning approach.

BMC psychiatry Jul 15, 2025
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Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters.

Scientific reports Jul 15, 2025
Random forest models have demonstrated utility in the determination of New York Heart Association (NYHA) Heart Failure Classifications. This study aims to determine the prediction accuracy of a random forest model to derive NYHA Classification from m... read more 
Humans Students, Medical Heart Failure Patient Simulation

BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.

BMC biology Jul 15, 2025
BACKGROUND: Diabetes is a global metabolic disease that urgently calls for the development of new and effective therapeutic agents. Anti-diabetic peptides (ADPs) have emerged as a research hotspot due to their therapeutic potential and natural safety... read more 
Humans Peptides Computational Biology Hypoglycemic Agents

Predictive modeling for step II therapy response in periodontitis - model development and validation.

NPJ digital medicine Jul 15, 2025
Steps I and II periodontal therapy is the first-line treatment for periodontal disease, but has varying success. This study aimed to develop machine learning models to predict changes in periodontal probing depth (PPD) after step II therapy using pat... read more 

Machine learning improves post-transplantation hepatocellular carcinoma recurrence prediction.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society Jul 15, 2025
BACKGROUND: To enhance post-transplantation hepatocellular carcinoma (HCC) recurrence prediction by evaluating additional novel risk factors and leveraging state-of-the-art machine learning (ML) algorithms. read more 
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