Systems Biology in Cancer Diagnosis Integrating Omics Technologies and Artificial Intelligence to Support Physician Decision Making

Abstract

Cancer is the second major cause of disease-related death worldwide, and its accurate early diagnosis and therapeutic intervention are fundamental for saving the patient’s life. Cancer, as a complex and heterogeneous disorder, results from the disruption and alteration of a wide variety of biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites, that eventually emerge as clinical symptoms. Traditionally, diagnosis is based on clinical examination, blood tests for biomarkers, the histopathology of a biopsy, and imaging (MRI, CT, PET, and US). Additionally, omics biotechnologies help to further characterize the genome, metabolome, microbiome traits of the patient that could have an impact on the prognosis and patient’s response to the therapy. The integration of all these data relies on gathering of several experts and may require considerable time, and, unfortunately, it is not without the risk of error in the interpretation and therefore in the decision. Systems biology algorithms exploit Artificial Intelligence (AI) combined with omics technologies to perform a rapid and accurate analysis and integration of patient’s big data, and support the physician in making diagnosis and tailoring the most appropriate therapeutic intervention. However, AI is not free from possible diagnostic and prognostic errors in the interpretation of images or biochemical–clinical data. Here, we first describe the methods used by systems biology for combining AI with omics and then discuss the potential, challenges, limitations, and critical issues in using AI in cancer research.

Joint Expedition: Exploring the Intersection of Digital Health and AI in Precision Medicine with Team Integration

“…This Special Issue has successfully achieved a significant milestone, featuring 20 contributions (Co)s (excluding this editorial) [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28].…”

“…The published papers (see Figure 1), according to the selected categories, encompass 1 introductory editorial [9], 7 full scientific articles [10][11][12][13][14][15][16], 5 reviews [17][18][19][20][21], 2 systematic reviews [22,23], 4 perspectives [24][25][26][27], and 1 opinion article [28].…”

“…Fawaz et al [20] propose a review that recalls how cancer is a leading cause of global disease-related death, emphasizing the importance of accurate early diagnosis and intervention. Traditional diagnostic methods include clinical examination, biomarker blood tests, biopsy histopathology, and imaging.…”

“…Twenty distinct contributions [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] weave through the intricate fields of the health domain focused on the integration of digital health and AI with precision medicine. These studies, spanning diverse medical domains, collectively leverage several AI and digital health approaches to precision medicine.…”

“…Transitioning to review studies [17][18][19][20][21], they play a critical role in providing essential scientific insights into the consolidation of themes. Importantly, these reviews highlight the pivotal role of AI in shaping the landscape of precision medicine, emphasizing its significance in guiding the current trajectory of research and knowledge consolidation.…”