Search Tag: deep learning models
2025 06 Jul
Breast cancer is the most frequently diagnosed cancer among women worldwide. Mammographic screening remains a key strategy in early detection, helping reduce mortality and morbidity. However, limitations such as false-positive and false-negative results, overdiagnosis and radiologist workload continue to challenge screening programmes. Furthermore,...Read more
2025 25 May
The emergence of digital medicine has been tightly interwoven with the proliferation of deep learning models, which require extensive and diverse datasets for effective development and validation. However, stringent privacy regulations, particularly in healthcare, limit the accessibility and sharing of real patient data. This tension between data...Read more
2025 30 Mar
The integration of artificial intelligence in radiology has rapidly advanced, offering significant potential for predictive diagnostics and personalised care. However, the clinical reliability of these models hinges on their transparency and reproducibility, particularly through independent external validation. Despite growing emphasis on open science,...Read more
2025 10 Jan
The continuous advancement of healthcare technology has driven the industry to explore innovative methods for improving patient care and operational efficiency. One significant area of focus is the evolution of electronic health record (EHR) systems, which have become integral to modern medical practice. Among the promising innovations contributing...Read more
2025 10 Jan
Artificial Intelligence (AI) has revolutionised the field of histopathology, particularly through deep learning (DL) models that assist in medical diagnostics. However, while most research focuses on improving the diagnostic accuracy of these models, the environmental impact of their development and usage has been largely overlooked. The high...Read more
2024 14 Oct
Brain MRI scans are essential for diagnosing a wide array of neurological conditions. However, analysing these images requires substantial expertise, and even experienced radiologists can face challenges in detecting subtle lesions due to the complexity of brain structures. This complexity has prompted the integration of deep learning (DL) models to...Read more