An investigative analysis - ChatGPT's capability to excel in the Polish speciality exam in pathology.

This study evaluates the effectiveness of the ChatGPT-3.5 language model in providing correct answers to pathomorphology questions as required by the State Speciality Examination (PES). Artificial intelligence (AI) in medicine is generating increasing interest, but its potential needs thorough evaluation.

Measurement of Cardiothoracic Ratio on Chest X-rays Using Artificial Intelligence-A Systematic Review and Meta-Analysis.

Chest X-rays (CXRs) are pivotal in clinical diagnostics, particularly in assessing cardiomegaly through the cardiothoracic ratio (CTR). This systematic review and meta-analysis evaluate the efficacy of artificial intelligence (AI) in automating CTR determination to enhance patient care and streamline diagnostic processes. They are concentrated on comparing the performance of AI models in determining the CTR against human assessments, identifying the most effective models for potential clinical implementation.

Multi-Label Classification of Chest X-ray Abnormalities Using Transfer Learning Techniques.

In recent years, deep neural networks have enabled countless innovations in the field of image classification. Encouraged by success in this field, researchers worldwide have demonstrated how to use Convolutional Neural Network techniques in medical imaging problems. In this article, the results were obtained through the use of the EfficientNet in the task of classifying 14 different diseases based on chest X-ray images coming from the NIH (National Institutes of Health) ChestX-ray14 dataset.