AI Medical Compendium Journal:
Medicine

Showing 11 to 20 of 235 articles

Identification of a telomere-related gene signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma by integrated analysis of machine learning and Mendelian randomization.

Medicine
Telomere-related genes (TRGs) are vital in diverse tumor types. Nevertheless, there is a notable lack of in-depth research concerning their significance in head and neck squamous cell carcinoma (HNSCC). In this context, the present study aims to asse...

Assessing the quality and readability of patient education materials on chemotherapy cardiotoxicity from artificial intelligence chatbots: An observational cross-sectional study.

Medicine
Artificial intelligence (AI) and the introduction of Large Language Model (LLM) chatbots have become a common source of patient inquiry in healthcare. The quality and readability of AI-generated patient education materials (PEM) is the subject of man...

Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Medicine
Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early diagnosis and personalized treatment. Th...

Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.

Medicine
In the contemporary fight against cancer, primary health care (PHC) services hold a significant and critical position within the healthcare system. This study, as one of the most detailed investigations into cancer research in primary care, comprehen...

Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.

Medicine
The aim of this study was to devise a machine learning algorithm with superior performance in predicting bone metastasis (BM) in small cell lung cancer (SCLC) and create a straightforward web-based predictor based on the developed algorithm. Data com...

Readability, reliability and quality of responses generated by ChatGPT, gemini, and perplexity for the most frequently asked questions about pain.

Medicine
It is clear that artificial intelligence-based chatbots will be popular applications in the field of healthcare in the near future. It is known that more than 30% of the world's population suffers from chronic pain and individuals try to access the h...

Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms.

Medicine
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients w...

Machine learning-based risk assessment for cardiovascular diseases in patients with chronic lung diseases.

Medicine
The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to ...

A semi-supervised learning approach to classify drug attributes in a pharmacy management database: A STROBE-compliant study.

Medicine
With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these technologies. Our study aims to enhance the accuracy of drug attribute classification and recommend appro...

Screening of mitochondrial-related biomarkers connected with immune infiltration for acute respiratory distress syndrome through WGCNA and machine learning.

Medicine
Septic acute respiratory distress syndrome (ARDS) is a complex and noteworthy type, but its molecular mechanism has not been fully elucidated. The aim is to explore specific biomarkers to diagnose sepsis-induced ARDS. Gene expression data of sepsis a...