Na IT2025 IEEE konferenciji na Žabljaku, istraživači sa Univerziteta Donja Gorica predstavili su svoju najnoviju studiju o korištenju vještačke inteligencije (AI) za dijagnostiku raka dojke. Istraživanje istražuje primjenu modela dubokog učenja, ResNet152 i DenseNet121, za analizu mamografskih slika. Osim kliničkih rezultata, studija naglašava implikacije korištenja računarske infrastrukture visokih performansi (HPC) kako bi se optimizirala obuka i evaluacija modela. Prenošenjem eksperimentalne postavke na HPC resurse, istraživanje otvara puteve za brže razvojne cikluse, istraživanje složenijih arhitektura i skalabilnost za implementaciju u stvarnom svijetu.
ABSTRACT – Artificial Intelligence is rapidly advancing the medical field by providing innovative disease diagnosis, treatment, and research approaches. This study explores the application of artificial intelligence in breast cancer diagnostics, focusing on using convolutional neural networks and deep learning to analyze mammographic images. ResNet152 and DenseNet121 models were used to classify malignant changes, achieving AUC scores exceeding 0.9, demonstrating their clinical utility. The research emphasizes how artificial intelligence can enhance screening efficiency, expedite diagnostic processes, and facilitate personalized treatment approaches. Ethical considerations, including patient safety and the transparency of artificial intelligence systems, were also analyzed. The findings underscore the potential of artificial intelligence to transform diagnostic procedures for breast cancer and highlight the importance of further research to integrate these technologies into clinical practice.
