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AI-Enabled Lung Cancer Prognosis
[article]
2024
arXiv
pre-print
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Among these, Non-Small Cell Lung Cancer (NSCLC) is the predominant subtype, characterized by a notably bleak prognosis and low overall survival rate of approximately 25% over five years across all disease ...
Recent advancements in artificial intelligence (AI) have revolutionized the landscape of lung cancer prognosis. ...
The imaging-based applications of deep neural networks showed significant improvements in all aspects of lung cancer prognosis. ...
arXiv:2402.09476v1
fatcat:atoy3fej2rgu3n72et3dq2fpom
Deep Learning Model as a New Trend in Computer-aided Diagnosis of Tumor Pathology for Lung Cancer
2020
Journal of Cancer
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In this review, we will introduce the application, progress and problems of deep learning in pathology of lung cancer and make prospects for its future development. ...
Lung cancer is one of the main causes of cancer-related death in the world. ...
Zhenxiang Chen, Vice Dean of College of Information Science and Engineering, Jinan University, for his excellent suggestion and assist work for this manuscript. ...
doi:10.7150/jca.43268
pmid:32284758
pmcid:PMC7150458
fatcat:5lq3sjp2z5ecbomw43ab5howzy
A narrative review of artificial intelligence-assisted histopathologic diagnosis and decision-making for non-small cell lung cancer: achievements and limitations
2021
Journal of Thoracic Disease
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More advanced deep learning for classifying pathologic images with minimal human interactions has been developed in addition to the conventional machine learning scheme. ...
Lung cancer is one of the most common cancers and the leading cause of cancer-related deaths worldwide. ...
carcinoma; NSCLC, non-small cell lung cancer; SCLC, small cell lung cancer; ASC, adenosquamous carcinoma; LC, large cell lung cancer ...
doi:10.21037/jtd-21-806
pmid:35070383
pmcid:PMC8743410
fatcat:k6mnyzlvxnfyhlmd7d2b2hsixe
Artificial intelligence-assisted decision making for prognosis and drug efficacy prediction in lung cancer patients: a narrative review
2021
Journal of Thoracic Disease
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These models have the potential to assist radiologists and oncologists in detecting lung cancer, predicting prognosis and developing personalized treatment plans for better outcomes of the patients. ...
AI, especially for those based on deep learning and radiomics, is capable of assisting clinical decision making from many aspects, for its quantitatively interpretation of patients' information and its ...
According to its histological classification, lung cancer consists of smallcell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) (1) . ...
doi:10.21037/jtd-21-864
pmid:35070384
pmcid:PMC8743400
fatcat:lrkxluf6zjh3daww2yu5htvfbe
Deep learning in cancer diagnosis, prognosis and treatment selection
2021
Genome Medicine
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We provide specific examples of how deep learning may be applied in cancer diagnosis, prognosis and treatment management. ...
We focus on the deep learning applications for omics data types, including genomic, methylation and transcriptomic data, as well as histopathology-based genomic inference, and provide perspectives on how ...
Acknowledgements Khoa Tran was the recipient of the Maureen and Barry Stevenson PhD Scholarship, we are grateful to Maureen Stevenson for her support. ...
doi:10.1186/s13073-021-00968-x
pmid:34579788
pmcid:PMC8477474
fatcat:y73fumwdazft3pw47gqdcncnue
Artificial Intelligence in Cancer Research and Precision Medicine
2021
Cancer Discovery
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Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has led to an explosion of AI use in various aspects ...
These applications range from detection and classification of cancer, to molecular characterization of tumors and their microenvironment, to drug discovery and repurposing, to predicting treatment outcomes ...
Elemento is supported by NIH grants UL1TR002384 and R01CA194547, and the Leukemia and Lymphoma Society Specialized Center of Research grants 180078-02 and 7021-20. ...
doi:10.1158/2159-8290.cd-21-0090
pmid:33811123
pmcid:PMC8034385
fatcat:x42n62qmrva2zodrxj4tf7bveq
Deep Learning Approaches in Histopathology
2022
Cancers
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The revolution of artificial intelligence and its impacts on our daily life has led to tremendous interest in the field and its related subtypes: machine learning and deep learning. ...
Scientists and developers have designed machine learning- and deep learning-based algorithms to perform various tasks related to tumor pathologies, such as tumor detection, classification, grading with ...
Acknowledgments: Alhassan Ali Ahmed and Mohamed Abouzid are participants of the STER Internationalization of Doctoral Schools Program from NAWA Polish National Agency for Academic Exchange No. ...
doi:10.3390/cancers14215264
pmid:36358683
pmcid:PMC9654172
fatcat:a5j6te3zifgsrmrdxjz76rvxw4
The future of artificial intelligence in thoracic surgery for non-small cell lung cancer treatment a narrative review
2024
Frontiers in Oncology
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ObjectivesTo present a comprehensive review of the current state of artificial intelligence (AI) applications in lung cancer management, spanning the preoperative, intraoperative, and postoperative phases.MethodsA ...
AI holds promise in managing lung cancer, challenges exist. ...
in early-stage non-small-cell lung cancer. ...
doi:10.3389/fonc.2024.1347464
pmid:38414748
pmcid:PMC10897973
fatcat:qemjpd232zfhzglgv6zmzan6kq
Advances in artificial intelligence to predict cancer immunotherapy efficacy
2023
Frontiers in Immunology
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This article focuses on the current prediction models based on information from histopathological slides, imaging-omics, genomics, and proteomics, and reviews their research progress and applications. ...
early implementation of AI-assisted diagnosis and treatment systems in the future. ...
All the figures in this article are made by Figdraw (www.figdraw.com) and Biorender (biorender.com). ...
doi:10.3389/fimmu.2022.1076883
pmid:36685496
pmcid:PMC9845588
fatcat:7pz4kvdsjjejjkv4de3yjjvqvi
The current issues and future perspective of artificial intelligence for developing new treatment strategy in non-small cell lung cancer: harmonization of molecular cancer biology and artificial intelligence
2021
Cancer Cell International
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of personalized medicine in non-small lung cancer. ...
The use of AI, such as machine learning approaches and deep learning systems, allows for the efficient analysis of massive omics data combined with accurate clinical information and can lead to comprehensive ...
in non-small-cell lung cancer. ...
doi:10.1186/s12935-021-02165-7
pmid:34446006
pmcid:PMC8393743
fatcat:ksvydxnfnnehfno2qbtdeagcgm
Editorial: RNA Modification in Human Cancers: Roles and Therapeutic Implications
2022
Frontiers in Genetics
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Lu et al. uncovered that miR-27a-3p modulated ferroptosis via targeting SLC7A11 in non-small cell lung cancer cells, implying the importance of miR-27a-3p/SLC7A11 in ferroptosis. ...
Accumulating research has witnessed the high frequency of m 6 A modification in cancers which could be used to predict diagnosis and prognosis of cancer patients (Chen et al., 2018) . ...
Yang et al. developed a deep convolutional neural network-based framework to evaluate efficacy of immunological therapy for lung cancer from histopathological images. ...
doi:10.3389/fgene.2022.845744
pmid:35173771
pmcid:PMC8841760
fatcat:pq65diwyfndjnovhhi2m6jwy4u
Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology
2020
Frontiers in Pharmacology
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of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. ...
Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. ...
MSI tool was used to identify unique region-of-interest-specific biomarkers (lipid signature) and therapeutic targets to classify colorectal cancer and subtyping in non-small cell lung cancer (Kriegsmann ...
doi:10.3389/fphar.2020.01177
pmid:32903628
pmcid:PMC7438594
fatcat:u7mdynhnwfazbn6jhvcagorp2a
What can artificial intelligence teach us about the molecular mechanisms underlying disease?
2019
European Journal of Nuclear Medicine and Molecular Imaging
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Non-small-cell lung cancer is used as an exemplar and the focus of this review as the most common tumour type in which AI and ML approaches have been tested and to illustrate some of the concepts. ...
in machine learning (ML). ...
, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...
doi:10.1007/s00259-019-04370-z
pmid:31190176
pmcid:PMC6879441
fatcat:q57b7kjlwzd7lnwcpp3iu7zbre
Deep Learning of Histopathology Images at the Single Cell Level
2021
Frontiers in Artificial Intelligence
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The spatial organization of these different cell types in TIME could be used as biomarkers for predicting drug responses, prognosis and metastasis. ...
Recently, deep learning approaches have been widely used for digital histopathology images for cancer diagnoses and prognoses. ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. ...
doi:10.3389/frai.2021.754641
pmid:34568816
pmcid:PMC8461055
fatcat:utnyq2nvmzbitkipjo6tpiuioq
In the literature: October 2020
2020
ESMO Open
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board or speaker fees from Merck Serono, Roche, Servier, Takeda and Astellas in the last 5 years. ...
Provenance and peer review Commissioned; internally peer reviewed. ...
are able, among others, to classify and predict mutations in lung and liver cancers, and to predict microsatellite instability in gastrointestinal cancer. ...
doi:10.1136/esmoopen-2020-001048
pmid:33037034
pmcid:PMC7549462
fatcat:a36jyjt42je4pasfrglyaq4dw4
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