In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …

Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …

Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …

The current diagnostic pathway for prostate cancer has resulted in overdiagnosis and
consequent overtreatment as well as underdiagnosis and missed diagnoses in many men …

Objectives: To investigate the current clinical applications and diagnostic performance of
artificial intelligence (AI) in dental and maxillofacial radiology (DMFR). Methods: Studies …

Prostate cancer is one of the most common forms of cancer in men in many countries. The
survival rate can be significantly enhanced with early detection of the cancer so that …

Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it
combines information from various imaging modalities to provide a more comprehensive …

Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …