A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine.

Background: In Persian medicine, early diagnosis and treatment of stomach dystemperament is crucial for preventing other diseases. However, traditional medicine diagnosis often involves ambiguous and less structured information making it challenging for practitioners. Integrating fuzzy ontology with case-based reasoning (CBR) systems can enhance diagnostic accuracy in this filed.

Evaluating the strengths and weaknesses of large language models in answering neurophysiology questions.

Large language models (LLMs), like ChatGPT, Google's Bard, and Anthropic's Claude, showcase remarkable natural language processing capabilities. Evaluating their proficiency in specialized domains such as neurophysiology is crucial in understanding their utility in research, education, and clinical applications. This study aims to assess and compare the effectiveness of Large Language Models (LLMs) in answering neurophysiology questions in both English and Persian (Farsi) covering a range of topics and cognitive levels.

Prediction of Diabetes Using Data Mining and Machine Learning Algorithms: A Cross-Sectional Study.

Objectives: This study aimed to develop a model to predict fasting blood glucose status using machine learning and data mining, since the early diagnosis and treatment of diabetes can improve outcomes and quality of life.

Methods: This crosssectional study analyzed data from 3376 adults over 30 years old at 16 comprehensive health service centers in Tehran, Iran who participated in a diabetes screening program. The dataset was balanced using random sampling and the synthetic minority over-sampling technique (SMOTE).

Ontology Engineering for Gastric Dystemperament in Persian Medicine.

Objective: Developing an ontology can help collecting and sharing information in traditional medicine including Persian medicine in a well-defined format. The present study aimed to develop an ontology for gastric dystemperament in the Persian medicine.

Methods: This was a mixed-methods study conducted in 2019.

Development and Evaluation of Ontologies in Traditional Medicine: A Review Study.

Background:  Development of ontologies in traditional medicine can be a foundation for other applications of informatics in this field. Despite the importance of the development of ontologies in traditional medicine, there are few review studies in this area. This study aims to review different methods for ontology development and evaluation in traditional medicine.

The Effects of WW2/WW3 Domains of Smurf2 Molecule on CD4+CD25+/CD4+ Proportion in Spleen of 4T1 Tumor Bearing BALB/c Mice.

Background: TGF-β has long been considered as the main inducer of Tregs in tumor microenvironment and is the reason for the aberrant number of Tregs in tumor-bearing individuals. Recently, it has been suggested that the enzyme arginase I is able to mediate the induction of Tregs in a TGF-β-independent fashion. The recombinant WW2/WW3 domains from smad ubiquitination regulatory factor 2 molecule was demonstrated to increase TGF-β signaling while reducing arginase I gene expression.