AIMC Topic: Machine Learning

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Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning.

BMC medical informatics and decision making
The diagnosis of pancreatic cancer presents a significant challenge due to the asymptomatic nature of the disease and the fact that it is frequently detected at an advanced stage. This study presents a novel approach combining graph-based data repres...

Machine learning modeling for predicting adherence to physical activity guideline.

Scientific reports
This study aims to create predictive models for PA guidelines by using ML and examine the critical determinants influencing adherence to the PA guidelines. 11,638 entries from the National Health and Nutrition Examination Survey were analyzed. Variab...

Application of artificial intelligence in forecasting survival in high-grade glioma: systematic review and meta-analysis involving 79,638 participants.

Neurosurgical review
High-grade glioma (HGG) is an aggressive brain tumor with poor survival rates. Predicting survival outcomes is critical for personalized treatment planning. In recent years, artificial intelligence (AI), particularly machine learning (ML) and deep le...

A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Biophysical chemistry
Interest in HDAC3 inhibitors (HDAC3i) for pharmacological applications outside of cancer is growing. However, concerns regarding the possible mutagenicity of the commonly used hydroxamates (zinc-binding groups, ZBGs) are also increasing. Considering ...

Prediction of thyroid malignancy risk using clinical and ultrasonography features and a machine learning approach.

European radiology
OBJECTIVE: This study aims to develop and validate a predictive model for thyroid nodule malignancy risks using clinical and ultrasonography features and a machine learning (ML) approach.

Identification of biomarkers associated with phagocytosis regulatory factors in coronary artery disease using machine learning and network analysis.

Mammalian genome : official journal of the International Mammalian Genome Society
BACKGROUND: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.

Dental Composite Performance Prediction Using Artificial Intelligence.

Journal of dental research
There is a need to increase the performance and longevity of dental composites and accelerate the translation of novel composites to the market. This study explores the use of artificial intelligence (AI), specifically machine learning (ML) models, t...

Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.

Cancer genetics
BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are used to predict outcomes in machine learning (ML). Recently, deep-learning methods have become applicable to image data converted from nonimage samples.

Finger-aware Artificial Neural Network for predicting arthritis in Patients with hand pain.

Artificial intelligence in medicine
Arthritis is an inflammatory condition associated with joint damage, the incidence of which is increasing worldwide. In severe cases, arthritis can result in the restriction of joint movement, thereby affecting daily activities; as such, early and ac...

From challenges and pitfalls to recommendations and opportunities: Implementing federated learning in healthcare.

Medical image analysis
Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centers while ensuring data privacy and security are not compromised. Although numerous recent studies suggest or utilize federate...