Bita Bayat

Catalyzing IVF outcome prediction: exploring advanced machine learning paradigms for enhanced success rate prognostication

Seyed‐Ali Sadegh‐Zadeh, Sanaz Khanjani, Shima Javanmardi, Bita Bayat et autres

Fertilization (IVF) success rate prediction by integrating advanced machine learning paradigms with gynecological expertise. The methodology involves the analysis of comprehensive datasets from 2017 to 2018 and 2010-2016. Machine learning models, including Logistic Regression, Gaussian NB, SVM, MLP, KNN, and ensemble models …

gb, ir, nl (code pays fourni par la source)

Precision diagnostics in cardiac tumours: Integrating echocardiography and pathology with advanced machine learning on limited data

Seyed‐Ali Sadegh‐Zadeh, Naser Khezerlouy‐Aghdam, Hanieh Sakha, Mehrnoush Toufan et autres

This study pioneers the integration of echocardiography and pathology data with advanced machine learning (ML) techniques to significantly enhance the diagnostic accuracy of cardiac tumours, a critical yet challenging aspect of cardiology. Despite advancements in diagnostic methods, cardiac tumours' nuanced complexity and …

gb, ir (code pays fourni par la source)

Role of Artificial Intelligence in the Diagnosis and Treatment of Diseases

Mehdi Rezaei, Erfan Rahmani, Soheila Jafari Khouzani, Maryam Rahmannia et autres

Artificial intelligence (AI) is rapidly transforming healthcare, and one of its most promising applications is in the diagnosis and treatment of diseases. AI algorithms can analyze vast amounts of medical data, identify patterns and insights that may not be apparent to human …