AI Medical Compendium Journal:
Experimental biology and medicine (Maywood, N.J.)

Showing 1 to 10 of 27 articles

Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review.

Experimental biology and medicine (Maywood, N.J.)
Attention deficit/hyperactivity disorder is a common neuropsychiatric disorder that affects around 5%-7% of children worldwide. Artificial intelligence provides advanced models and algorithms for better diagnosis, prediction and classification of att...

Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques.

Experimental biology and medicine (Maywood, N.J.)
Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overd...

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women.

Experimental biology and medicine (Maywood, N.J.)
Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the se...

Artificial intelligence in the diagnosis of uveal melanoma: advances and applications.

Experimental biology and medicine (Maywood, N.J.)
Advancements in machine learning and deep learning have the potential to revolutionize the diagnosis of melanocytic choroidal tumors, including uveal melanoma, a potentially life-threatening eye cancer. Traditional machine learning methods rely heavi...

Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study.

Experimental biology and medicine (Maywood, N.J.)
Screening tests for disease have their performance measured through sensitivity and specificity, which inform how well the test can discriminate between those with and without the condition. Typically, high values for sensitivity and specificity are ...

Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.

Experimental biology and medicine (Maywood, N.J.)
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic m...

Integrating artificial intelligence in strabismus management: current research landscape and future directions.

Experimental biology and medicine (Maywood, N.J.)
Advancements in artificial intelligence (AI) are transforming strabismus management through improved screening, diagnosis, and surgical planning. Deep learning has notably enhanced diagnostic accuracy and optimized surgical outcomes. Despite these ad...

A quantum-based oversampling method for classification of highly imbalanced and overlapped data.

Experimental biology and medicine (Maywood, N.J.)
Data imbalance is a challenging problem in classification tasks, and when combined with class overlapping, it further deteriorates classification performance. However, existing studies have rarely addressed both issues simultaneously. In this article...

Data-driven approach to quantify trust in medical devices using Bayesian networks.

Experimental biology and medicine (Maywood, N.J.)
Bayesian networks are increasingly used to quantify the uncertainty of subjective and stochastic concepts such as trust. In this article, we propose a data-driven approach to estimate Bayesian parameters in the domain of wearable medical devices. Our...