Literature DB >> 34020642

Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future.

Muhammad Javed Iqbal1, Zeeshan Javed2, Haleema Sadia3, Ijaz A Qureshi4, Asma Irshad5, Rais Ahmed6, Kausar Malik7, Shahid Raza8, Asif Abbas1, Raffaele Pezzani9,10, Javad Sharifi-Rad11,12.   

Abstract

Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.

Entities:  

Keywords:  Artificial intelligence; Cancer diagnosis; Machine learning; Therapeutic interventions; Treatment

Year:  2021        PMID: 34020642     DOI: 10.1186/s12935-021-01981-1

Source DB:  PubMed          Journal:  Cancer Cell Int        ISSN: 1475-2867            Impact factor:   5.722


  40 in total

Review 1.  Application of surgical safety standards to robotic surgery: five principles of ethics for nonmaleficence.

Authors:  Jeffrey A Larson; Michael H Johnson; Sam B Bhayani
Journal:  J Am Coll Surg       Date:  2013-11-12       Impact factor: 6.113

2.  Redesigning gender identity services: an opportunity to generate evidence.

Authors:  Richard Byng; Susan Bewley; Damian Clifford; Margaret McCartney
Journal:  BMJ       Date:  2018-10-29

3.  EnsembleGASVR: a novel ensemble method for classifying missense single nucleotide polymorphisms.

Authors:  Trisevgeni Rapakoulia; Konstantinos Theofilatos; Dimitrios Kleftogiannis; Spiros Likothanasis; Athanasios Tsakalidis; Seferina Mavroudi
Journal:  Bioinformatics       Date:  2014-04-26       Impact factor: 6.937

Review 4.  Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

Authors:  Jenna Wiens; Erica S Shenoy
Journal:  Clin Infect Dis       Date:  2018-01-06       Impact factor: 9.079

5.  Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

Authors:  Konstantinos Theofilatos; Niki Pavlopoulou; Christoforos Papasavvas; Spiros Likothanassis; Christos Dimitrakopoulos; Efstratios Georgopoulos; Charalampos Moschopoulos; Seferina Mavroudi
Journal:  Artif Intell Med       Date:  2015-02-18       Impact factor: 5.326

Review 6.  Artificial intelligence in healthcare: past, present and future.

Authors:  Fei Jiang; Yong Jiang; Hui Zhi; Yi Dong; Hao Li; Sufeng Ma; Yilong Wang; Qiang Dong; Haipeng Shen; Yongjun Wang
Journal:  Stroke Vasc Neurol       Date:  2017-06-21

7.  NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer.

Authors:  Irantzu Anzar; Angelina Sverchkova; Richard Stratford; Trevor Clancy
Journal:  BMC Med Genomics       Date:  2019-05-16       Impact factor: 3.063

8.  Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

Authors:  Nathan Wan; David Weinberg; Tzu-Yu Liu; Katherine Niehaus; Eric A Ariazi; Daniel Delubac; Ajay Kannan; Brandon White; Mitch Bailey; Marvin Bertin; Nathan Boley; Derek Bowen; James Cregg; Adam M Drake; Riley Ennis; Signe Fransen; Erik Gafni; Loren Hansen; Yaping Liu; Gabriel L Otte; Jennifer Pecson; Brandon Rice; Gabriel E Sanderson; Aarushi Sharma; John St John; Catherina Tang; Abraham Tzou; Leilani Young; Girish Putcha; Imran S Haque
Journal:  BMC Cancer       Date:  2019-08-23       Impact factor: 4.430

Review 9.  Robotic Surgery in Gynecology.

Authors:  Jean Bouquet de Joliniere; Armando Librino; Jean-Bernard Dubuisson; Fathi Khomsi; Nordine Ben Ali; Anis Fadhlaoui; J M Ayoubi; Anis Feki
Journal:  Front Surg       Date:  2016-05-02
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  13 in total

Review 1.  Applications of artificial intelligence multiomics in precision oncology.

Authors:  Ruby Srivastava
Journal:  J Cancer Res Clin Oncol       Date:  2022-07-07       Impact factor: 4.553

Review 2.  Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis.

Authors:  Valentina Russo; Eleonora Lallo; Armelle Munnia; Miriana Spedicato; Luca Messerini; Romina D'Aurizio; Elia Giuseppe Ceroni; Giulia Brunelli; Antonio Galvano; Antonio Russo; Ida Landini; Stefania Nobili; Marcello Ceppi; Marco Bruzzone; Fabio Cianchi; Fabio Staderini; Mario Roselli; Silvia Riondino; Patrizia Ferroni; Fiorella Guadagni; Enrico Mini; Marco Peluso
Journal:  Cancers (Basel)       Date:  2022-08-19       Impact factor: 6.575

Review 3.  Role of smartphone devices in precision oncology.

Authors:  Ruby Srivastava
Journal:  J Cancer Res Clin Oncol       Date:  2022-10-17       Impact factor: 4.322

4.  Artificial Intelligence and Machine Learning in Cancer Research: A Systematic and Thematic Analysis of the Top 100 Cited Articles Indexed in Scopus Database.

Authors:  Ibrahim H Musa; Lukman O Afolabi; Ibrahim Zamit; Taha H Musa; Hassan H Musa; Andrew Tassang; Tosin Y Akintunde; Wei Li
Journal:  Cancer Control       Date:  2022 Jan-Dec       Impact factor: 2.339

Review 5.  Gaps and Opportunities of Artificial Intelligence Applications for Pediatric Oncology in European Research: A Systematic Review of Reviews and a Bibliometric Analysis.

Authors:  Alberto Eugenio Tozzi; Francesco Fabozzi; Megan Eckley; Ileana Croci; Vito Andrea Dell'Anna; Erica Colantonio; Angela Mastronuzzi
Journal:  Front Oncol       Date:  2022-05-31       Impact factor: 5.738

6.  Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer.

Authors:  Tenghui Han; Jun Zhu; Xiaoping Chen; Rujie Chen; Yu Jiang; Shuai Wang; Dong Xu; Gang Shen; Jianyong Zheng; Chunsheng Xu
Journal:  Cancer Cell Int       Date:  2022-01-15       Impact factor: 5.722

7.  A Convolutional Neural Network-Based Intelligent Medical System with Sensors for Assistive Diagnosis and Decision-Making in Non-Small Cell Lung Cancer.

Authors:  Xiangbing Zhan; Huiyun Long; Fangfang Gou; Xun Duan; Guangqian Kong; Jia Wu
Journal:  Sensors (Basel)       Date:  2021-11-30       Impact factor: 3.576

8.  Machine learning predicts cancer subtypes and progression from blood immune signatures.

Authors:  David A Simon Davis; Sahngeun Mun; Julianne M Smith; Dillon Hammill; Jessica Garrett; Katharine Gosling; Jason Price; Hany Elsaleh; Farhan M Syed; Ines I Atmosukarto; Benjamin J C Quah
Journal:  PLoS One       Date:  2022-02-28       Impact factor: 3.240

Review 9.  Irradiation immunity interactions.

Authors:  David A Simon Davis; Ines I Atmosukarto; Jessica Garrett; Katharine Gosling; Farhan M Syed; Ben Jc Quah
Journal:  J Med Imaging Radiat Oncol       Date:  2022-03-08       Impact factor: 1.667

10.  Cohort Profile: Chinese Cervical Cancer Clinical Study.

Authors:  Xi-Ru Zhang; Zhi-Qiang Li; Li-Xin Sun; Ping Liu; Zhi-Hao Li; Peng-Fei Li; Hong-Wei Zhao; Bi-Liang Chen; Mei Ji; Li Wang; Shan Kang; Jing-He Lang; Chen Mao; Chun-Lin Chen
Journal:  Front Oncol       Date:  2021-06-18       Impact factor: 6.244

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