As the burgeoning field of Artificial Intelligence (AI) continues to permeate the fabric of
healthcare, particularly in the realms of patient surveillance and telemedicine, a …

Simple Summary Recently, radiogenomics has played a significant role and offered a new
understanding of cancer's biology and behavior in response to standard therapy. It also …

Abstract Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in
oncology. Recently, several machine learning (ML) techniques have been adapted for this …

Simple Summary Oral cancer is characterized by high morbidity and mortality, since the
disease is typically in an advanced locoregional stage at the time of diagnosis. The …

Machine learning-based tools are capable of guiding individualized clinical management
and decision-making by providing predictions of a patient's future health state. Through their …

Resistance to therapy remains a major cause of cancer treatment failures, resulting in many
cancer-related deaths. Resistance can occur at any time during the treatment, even at the …

Monitoring survival of cancer patients using data collected by population‐based cancer
registries is an important component of cancer control. In this setting, patient survival is often …

Purpose To systematically review and evaluate the methodological quality of studies using
radiomics for diagnostic and predictive purposes in patients with intracranial meningioma …

Background Atypical cartilaginous tumour (ACT) and grade II chondrosarcoma (CS2) of long
bones are respectively managed with watchful waiting or curettage and wide resection …

Objectives We aimed to assess the performance of radiomics and machine learning (ML) for
classification of non-cystic benign and malignant breast lesions on ultrasound images …