Artificial intelligence in oncology: current applications and future perspectives

Abstract

Artificial intelligence (AI) is concretely reshaping the landscape and horizons of oncology, opening new important opportunities for improving the management of cancer patients. Analysing the AI-based devices that have already obtained the official approval by the Federal Drug Administration (FDA), here we show that cancer diagnostics is the oncology-related area in which AI is already entered with the largest impact into clinical practice. Furthermore, breast, lung and prostate cancers represent the specific cancer types that now are experiencing more advantages from AI-based devices. The future perspectives of AI in oncology are discussed: the creation of multidisciplinary platforms, the comprehension of the importance of all neoplasms, including rare tumours and the continuous support for guaranteeing its growth represent in this time the most important challenges for finalising the ‘AI-revolution’ in oncology.

Artificial Intelligence for Predicting Microsatellite Instability Based on Tumor Histomorphology: A Systematic Review

“…Over the past decade, research on AI-based diagnostic tests has been centered on AI research in the healthcare field. Of note, more than 90% of health-related AI systems that have received regulatory evaluation from the US Food and Drug Administration are related to the diagnostic field [ 27 ]. Although AI-based diagnostic research is carried out extensively, the existing QUADAS-2 tool for evaluating diagnostic research may be not sufficient to reflect the specificity of such a heterogeneous field, so it may be of help to consider the modified quality’s evaluation tools.…”

“…However, such attempts to predict MSI by histomorphology by humans have not achieved enough accuracy to replace existing methods. Recently, with the rapid development of artificial intelligence (AI), the ability to identify histomorphological patterns or characteristics for recognizing tumor molecular subtypes and for predicting the prognosis of diseases has been advanced [ 25 , 26 , 27 , 28 , 29 , 30 ]. Compared to humans, AI can detect subtle morphologic features that cannot be detected by the human eye.…”

Artificial intelligence opportunities in cardio-oncology: Overview with spotlight on electrocardiography

“…Various AI techniques have been applied in cardiology [ 32 – 34 , 71 , 76 – 83 ] and oncology [ 84 , 85 ] and are now also being used in cardio-oncology ( Table 5 ). The most frequently used techniques in ML and DL generally fall within the two primary categories of ‘supervised learning’ and ‘unsupervised learning’.…”

Cardiovascular Diseases in the Digital Health Era: A Translational Approach from the Lab to the Clinic

“…BioTech 2022, 3, x FOR PEER REVIEW 2 of 15 [1], segmenting images [2], or prognosis prediction [3] and translate into a higher efficiency of the processes by reducing time and costs. Moreover, cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17,9 million lives each year, corresponding to 32% of all global deaths [5,6].…”

“…On this matter, the inherent capabilities of AI allow researchers to collect and interpret data relationships in digitalized clinical records that can reveal hidden information for the clinician with an inestimable impact in oncology [2], neurology [3], and cardiology fields [4], among others. These capabilities include the automation of tasks such as processing [1], segmenting images [2], or prognosis prediction [3] and translate into a higher efficiency of the processes by reducing time and costs. Moreover, cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17,9 million lives each year, corresponding to 32% of all global deaths [5,6].…”