AIMC Topic: Humans

Clear Filters Showing 17741 to 17750 of 95995 articles

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

International journal of legal medicine
Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The advantages of objectivity and non-invasiveness make computing tomography (CT) imaging an potential ...

Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.

Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial.

European journal of clinical investigation
BACKGROUND: The prediction of ischaemic stroke in patients with heart failure with reduced ejection fraction (HFrEF) but without atrial fibrillation (AF) remains challenging. Our aim was to evaluate the performance of machine learning (ML) in identif...

Reconsidering learnable fine-grained text prompts for few-shot anomaly detection in visual-language models.

Neural networks : the official journal of the International Neural Network Society
Few-Shot Anomaly Detection (FSAD) in industrial images aims to identify abnormalities using only a few normal images, which is crucial for industrial scenarios where sample training is limited. The recent advances in large-scale pre-trained visual-la...

Artificial intelligence in assessing progression of age-related macular degeneration.

Eye (London, England)
The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising pa...

Current status and future direction of cancer research using artificial intelligence for clinical application.

Cancer science
The expectations for artificial intelligence (AI) technology have increased considerably in recent years, mainly due to the emergence of deep learning. At present, AI technology is being used for various purposes and has brought about change in socie...

MMD-Net: Image domain multi-material decomposition network for dual-energy CT imaging.

Medical physics
BACKGROUND: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.

Diagnosis and typing of leukemia using a single peripheral blood cell through deep learning.

Cancer science
Leukemia is highly heterogeneous, meaning that different types of leukemia require different treatments and have different prognoses. Current clinical diagnostic and typing tests are complex and time-consuming. In particular, all of these tests rely ...

Development of a survey-based stacked ensemble predictive model for autonomy preferences in patients with periodontal disease.

Journal of dentistry
OBJECTIVES: This study aimed to develop a model to predict the autonomy preference (AP) and satisfaction after tooth extraction (STE) in patients with periodontal disease. Understanding of individual AP and STE is essential for improving patient sati...

Machine learning in image-based outcome prediction after radiotherapy: A review.

Journal of applied clinical medical physics
The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications in various...