scholarly journals Artificial Intelligence in Cancer Research

2021 ◽  
Vol 01 (1) ◽  
pp. 6-8
Author(s):  
Chandra Kishore ◽  
◽  
Priyanka Bhadra ◽  

The analytical power of artificial intelligence can revolutionize the field of cancer research, diagnosis, and treatment by analyzing the huge raw data available in biomedical science. In this review, we have discussed current challenges, development, and future perspectives of artificial intelligence in cancer research.

2019 ◽  
Vol 31 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Shin‐ei Kudo ◽  
Yuichi Mori ◽  
Masashi Misawa ◽  
Kenichi Takeda ◽  
Toyoki Kudo ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 493
Author(s):  
Riccardo Di Fiore ◽  
Sherif Suleiman ◽  
Bridget Ellul ◽  
Sharon A. O’Toole ◽  
Charles Savona-Ventura ◽  
...  

More than 50% of all gynecologic tumors can be classified as rare (defined as an incidence of ≤6 per 100,000 women) and usually have a poor prognosis owing to delayed diagnosis and treatment. In contrast to almost all other common solid tumors, the treatment of rare gynecologic tumors (RGT) is often based on expert opinion, retrospective studies, or extrapolation from other tumor sites with similar histology, leading to difficulty in developing guidelines for clinical practice. Currently, gynecologic cancer research, due to distinct scientific and technological challenges, is lagging behind. Moreover, the overall efforts for addressing these challenges are fragmented across different European countries and indeed, worldwide. The GYNOCARE, COST Action CA18117 (European Network for Gynecological Rare Cancer Research) programme aims to address these challenges through the creation of a unique network between key stakeholders covering distinct domains from concept to cure: basic research on RGT, biobanking, bridging with industry, and setting up the legal and regulatory requirements for international innovative clinical trials. On this basis, members of this COST Action, (Working Group 1, “Basic and Translational Research on Rare Gynecological Cancer”) have decided to focus their future efforts on the development of new approaches to improve the diagnosis and treatment of RGT. Here, we provide a brief overview of the current state-of-the-art and describe the goals of this COST Action and its future challenges with the aim to stimulate discussion and promote synergy across scientists engaged in the fight against this rare cancer worldwide.


2019 ◽  
Vol 47 (3) ◽  
pp. 362-368 ◽  
Author(s):  
Jeff Shrager ◽  
Mark Shapiro ◽  
William Hoos

Global Cumulative Treatment Analysis (GCTA) is a novel clinical research model combining expert knowledge, and treatment coordination based upon global information-gain, to treat every patient optimally while efficiently searching the vast space that is the realm of cancer research.


Author(s):  
Alberto Mangano ◽  
Valentina Valle ◽  
Nicolas Dreifuss ◽  
Gabriela Aguiluz ◽  
Mario Masrur

AI (Artificial intelligence) is an interdisciplinary field aimed at the development of algorithms to endow machines with the capability of executing cognitive tasks. The number of publications regarding AI and surgery has increased dramatically over the last two decades. This phenomenon can partly be explained by the exponential growth in computing power available to the largest AI training runs. AI can be classified into different sub-domains with extensive potential clinical applications in the surgical setting. AI will increasingly become a major component of clinical practice in surgery. The aim of the present Narrative Review is to give a general introduction and summarized overview of AI, as well as to present additional remarks on potential surgical applications and future perspectives in surgery.


2019 ◽  
Vol 51 (9) ◽  
pp. 1350-1352
Author(s):  
Christopher A. Lovejoy ◽  
Bruce Keogh ◽  
Mahiben Maruthappu

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