The spine journal : official journal of the North American Spine Society
Jan 11, 2025
BACKGROUND: In clinical practice, distinguishing between spinal tuberculosis (STB) and spinal tumors (ST) poses a significant diagnostic challenge. The application of AI-driven large language models (LLMs) shows great potential for improving the accu...
OBJECTIVE: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
AIMS: Left ventricular hypertrophy (LVH) is a common clinical finding associated with adverse cardiovascular outcomes. Once LVH is diagnosed, defining its cause has crucial clinical implications. Artificial intelligence (AI) may allow significant pro...
IntroductionThe prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) ...
BACKGROUND: Early diagnosis of syphilis is vital for its effective control. This study aimed to develop an Artificial Intelligence (AI) diagnostic model based on radiomics technology to distinguish early syphilis from other clinical skin lesions.
Bladder, kidney, and prostate cancers are prevalent urinary cancers, and developing efficient detection methods is of significance for the early diagnosis of them. However, noninvasive and sensitive detection of urinary cancers still challenges tradi...
RATIONALE AND OBJECTIVES: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.
As per world health organization, Anemia is a most prevalent blood disorder all over the world. Reduced number of Red Blood Cells or decrease in the number of healthy red blood cells is considered as Anemia. This condition also leads to the decrease ...
Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significant management implications. We assessed the performance of radiomics-based models in distinguishing ...
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breas...
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