Microfluidic Technology, Artificial Intelligence, and Biosensors As Advanced Technologies in Cancer Screening: A Review Article

Abstract

Cancer screening techniques aim to detect premalignant lesions and enable early intervention to delay the onset of cancer while keeping incidence constant. Technology advancements have led to the development of powerful tools such as microfluidic technology, artificial intelligence, machine learning algorithms, and electrochemical biosensors to aid in early cancer detection. Non-invasive cancer screening methods like virtual colonoscopy and endoscopic ultrasonography have also been developed to provide comprehensive pictures of organs and detect cancer early. This review article provides an overview of recent advances in cancer screening in microfluidic technology, artificial intelligence, and biomarkers through a narrative literature search. Microfluidic devices enable easy handling of sub-microliter volumes and have become a promising tool for cancer detection, drug screening, and modeling angiogenesis and metastasis in cancer research. Machine learning and artificial intelligence have shown high accuracy in oncology-related diagnostic imaging, reducing the manual steps in lesion detection and providing standardized and accurate results, with potential for global standardization in areas like colon polyps, breast cancer, and primary and metastatic brain cancer. A biomarker-based cancer diagnosis is promising for early detection and effective therapy, and electrochemical biosensors integrated with nanoparticles offer multiplexing and amplification capabilities. Understanding these advanced technologies' basics, achievements, and challenges is crucial for advancing their use in oncology.

Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics

“…The domain of CRC diagnosis has witnessed noteworthy progressions, notably in the realm of microfluidics as a promising and rapidly evolving field. This section aims to elucidate the manifold applications and advantages of microfluidics in CRC diagnostics [75].…”

“…These AI algorithms are meticulously trained to process the data, extract relevant features, and make predictions based on patterns and models derived from extensive datasets. What sets AI apart is its capacity for continuous learning and adaptability, leading to heightened diagnostic accuracy and efficiency [75]. The amalgamation of microfluidic systems and AI algorithms holds great promise for enhancing diagnostic capabilities, promising earlier and more precise disease detection, as schematically represented in Figure 7.…”

“…Furthermore, AI has evolved into a valuable tool for the identification of novel biomarker targets in CRC. Leveraging vast genomics and transcriptomics datasets, AI algorithms demonstrate proficiency in unveiling intricate patterns and associations that may elude human researchers due to their complexity and scale [75]. This computational approach streamlines the identification of potential biomarkers crucial for early detection and prognostic assessment in CRC.…”

Breast Cancer Screening Using Artificial Intelligence Techniques: Enhancing Biochemical Insights and Diagnostic Accuracy

“…Traditionally, invasive procedures and histopathological assessments, often involving Hematoxylin and Eosin (H&E) staining, were relied upon for diagnosis. However, AI has introduced a transformative shift in breast cancer screening, offering advanced diagnostic tools and improving patient care [5]. AI enables multi-scale correlations between medical imaging and gene expression data, providing increased accuracy and personalised treatment recommendations, particularly in radio-genomics [6].…”