Artificial Intelligence Medical Compendium

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

Showing 73,011 to 73,020 of 235,381 articles

When Health Behavior Meets Technology: Artificial Neural Network-Based Prediction of Breast Self-Examination Intentions Among Filipino Female College Students.

Journal of cancer education : the official journal of the American Association for Cancer Education
Early detection of breast cancer is crucial, particularly in low-resource settings. Emerging technologies like artificial neural networks (ANNs) offer innovative approaches to predict health behavior intentions. Hence, this study used an artificial n... read more 

Comment on 'Artificial Intelligence Chatbots as Virtual Patients in Dental Education: A Constructivist Approach to Classroom Implementation'.

European journal of dental education : official journal of the Association for Dental Education in Europe
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Evaluation of ChatGPT accuracy and reliability in answering questions about exercise recommendations for breast cancer survivors.

Physiotherapy
OBJECTIVE: To assess the accuracy and reliability of an artificial intelligence (AI) chatbot (ChatGPT) in providing answers about exercise recommendations for breast cancer survivors. DESIGN: Cross-sectional study. METHODS: We extracted recommendatio... read more 

Integration of multi-omics data and machine learning to identify antioxidant biomarkers in type 1 diabetes.

Free radical biology & medicine
The identification of biomarkers for early diagnosis and monitoring the progression of Type 1 Diabetes (T1DM) is essential for improving disease management. This study integrates multi-omics data with machine learning to identify antioxidant stress p... read more 

Temporal evolution stages classification and aging time prediction of gel-pen ink using GC-IMS combined with machine learning for forensic science applications.

Journal of chromatography. A
Determining the temporal evolution of inks remains a critical challenge in forensic document analysis. The temporal evolution stages classification and aging time prediction of gel-pen ink were investigated by integrating gas chromatography-ion mobil... read more 

An efficient and precise (micro)plastic identification method: feature infrared spectra extraction based on EIS-VIP-CARS and ANN modeling.

Environmental research
Understanding microplastics' (MPs) ecological impact necessitates their precise identification. To address the issue of the competitive adaptive reweighted sampling (CARS) algorithm extracting numerous feature wavenumber points (FWPs) that often miss... read more 

Managing waste for production of low-carbon concrete mix using uncertainty-aware machine learning model.

Environmental research
This study introduces an uncertainty-aware AI-driven optimization framework for designing sustainable concrete mixtures that incorporate waste-derived materials. The primary objectives are to reduce global warming potential (GWP) and promote a circul... read more 

The emerging role of artificial intelligence applied to exosome analysis: from cancer biology to other biomedical fields.

Life sciences
In recent years, exosomes versatility has prompted their study in the biomedical field for diagnostic, prognostic, and therapeutic applications. Exosomes are bi-lipid small extracellular vesicles (30-150 nm) secreted by various cell types, containing... read more 

A novel hybrid machine learning approach for accurate retrieval of ocean surface chlorophyll-a across oligotrophic to eutrophic waters.

Environmental research
Accurate assessment of chlorophyll a (Chla) concentration distribution and variations is significant for environmental monitoring and ecological research. However, the inversion of Chla in different optical types of water bodies can only be achieved ... read more 

Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Life sciences
Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However, assessing the clinical efficacy of chemotherapy drugs remains a challenging task. In recent years, ... read more