Artificial Intelligence Medical Compendium

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

Showing 2,661 to 2,670 of 235,381 articles

Data-Driven Prediction of Speech-in-Noise Performance: A Systematic Review and Meta-analysis of Machine Learning Models.

Annals of biomedical engineering
PURPOSE: Difficulty understanding speech in noise (SIN) is a major determinant of communication ability and quality of life, affecting individuals with hearing loss as well as some with normal hearing. Data-driven prediction methods offer a promising... read more 

A Likelihood-Based Framework for Simultaneously Learning Both Noise and Growth Dynamics Using Biologically-Informed Neural Networks.

Bulletin of mathematical biology
In recent years, neural ordinary differential equation frameworks such as Biologically-Informed Neural Networks (BINNs) have shown promise for learning mechanistic laws from sparse data. However, most existing approaches implicitly assume homoscedast... read more 

Artificial intelligence and machine learning in immunohematology: an expert overview of emerging tools for precision transfusion medicine.

Immunohematology
Artificial intelligence (AI) and machine learning (ML) are transforming immunohematology, offering significant enhancements in precision, accuracy, and personalized transfusion care. This expert overview summarizes current applications of AI/ML in ph... read more 

Optimizing Therapeutic Protocols: Insights from Neural Network Analysis of Fractional-Order Tumor Models.

Mathematical biosciences
This paper describes a mathematical model of tumor growth during chemotherapy, employing a fractional calculus approach to account for the interactions between cancer cells, normal cells, immune cells, and drugs. This method better reflects the role ... read more 

Precision medicine in MASLD: Integrating genetics, multi-omics, and artificial intelligence for risk stratification and targeted therapy.

Clinica chimica acta; international journal of clinical chemistry
Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly termed nonalcoholic fatty liver disease (NAFLD), encompasses a heterogeneous clinical spectrum ranging from isolated hepatic steatosis to metabolic dysfunction-associated stea... read more 

Managing Existing Pain: Predicting Pain Progression and Improvement Using Machine Learning Approaches.

Annals of epidemiology
PURPOSE: Chronic pain (CP) is highly prevalent in the U.S. and imposes substantial health and economic burdens. Understanding which biopsychosocial and treatment-related factors drive pain progression and improvement is essential for developing targe... read more 

Age-dependent brain mechanics are linked to microstructural changes.

Acta biomaterialia
Accurate knowledge of brain tissue mechanics is essential for understanding the pathologies that cause mechanical changes and for developing reliable computer models for neurosurgical procedures. However, the age-related changes in brain mechanics an... read more 

An integrated prediction model using machine learning and dynamics simulation for the selection of transdermal penetration enhancers.

Journal of controlled release : official journal of the Controlled Release Society
Penetration enhancers (PEs) are widely used in transdermal drug delivery systems (TDDS) due to their cost-effectiveness and excellent biocompatibility. However, the rapid selection of PEs for TDDS is hindered by two critical challenges: first, in vit... read more 

Large esophageal varices predict hepatocellular carcinoma in newly diagnosed cirrhosis: insights from machine learning and propensity score analysis.

Annals of hepatology
INTRODUCTION AND OBJECTIVES: Hepatocellular carcinoma (HCC) is a major complication of chronic liver disease (CLD) requiring improved risk stratification. Esophageal varices (EVs), as manifestations of severe portal hypertension, may promote HCC deve... read more 

Machine Learning-Based Brightfield Detection of Anti-Fibrotic Effects in a 3D Retinal Fibrosis Model.

SLAS discovery : advancing life sciences R & D
Three-dimensional (3D) spheroid and microtissue models are increasingly used in phenotypic drug discovery, yet their scalability for high-throughput screening often remains limited, constrained by the cost and complexity of conventional imaging-based... read more