Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate
information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer …

Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole-slide imaging allows …

Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of
digital pathology (DP) and an increase in computational power have led to the development …

Advancements in data acquisition and computational methods are generating a large
amount of heterogeneous biomedical data from diagnostic domains such as clinical …

Cancer is defined as a large group of diseases that is associated with abnormal cell growth,
uncontrollable cell division, and may tend to im**e on other tissues of the body by different …

Spatial multi-omic studies have emerged as a promising approach to comprehensively
analyze cells in tissues, enabling the joint analysis of multiple data modalities like …

The early detection of oral cancer is pivotal for improving patient survival rates. However, the
high cost of manual initial screenings poses a challenge, especially in resource-limited …

Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug
discovery and development, clinical trials, personalized medicine, pharmacogenomics …