Integration of artificial intelligence in lung cancer: Rise of the machine

Ladbury, Colton; Amini, Arya; Govindarajan, Ameish; Mambetsariev, Isa; Raz, Dan J.; Massarelli, Erminia; Williams, Terence M.; Rodin, Andréi S.; Salgia, Ravi

doi:10.1016/j.xcrm.2023.100933

Cited by 24 publications

(11 citation statements)

References 95 publications

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“…AI has the potential to improve the setting of clinical trials in several respects. First, the considerable progress offered by AI in cancer imaging and diagnosis should automatically produce a positive echo in clinical trial development [ 14 ]. Another advantage that AI has in clinical research is the simplification and speed of patient recruitment [ 15 ], particularly with the recent introduction of Chatbots like GPT-4 [ 16 ].…”

Section: Ai and Clinical Trial Developmentmentioning

confidence: 99%

Artificial Intelligence and Anticancer Drug Development—Keep a Cool Head

Bailleux,

Gal,

Chamorey

et al. 2024

Pharmaceutics

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Artificial intelligence (AI) is progressively spreading through the world of health, particularly in the field of oncology. AI offers new, exciting perspectives in drug development as toxicity and efficacy can be predicted from computer-designed active molecular structures. AI-based in silico clinical trials are still at their inception in oncology but their wider use is eagerly awaited as they should markedly reduce durations and costs. Health authorities cannot neglect this new paradigm in drug development and should take the requisite measures to include AI as a new pillar in conducting clinical research in oncology.

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Section: Ai and Clinical Trial Developmentmentioning

confidence: 99%

Artificial Intelligence and Anticancer Drug Development—Keep a Cool Head

Bailleux,

Gal,

Chamorey

et al. 2024

Pharmaceutics

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“…With regards to the specific focus of our review, AI-based technologies leverage vast data sources (i.e., patients' clinical records, imaging data, genomics, etc.) to identify potential biomarkers of prognosis, accurate prediction of treatment efficacy, and real-time monitoring of individualized responses, permitting tailored therapeutic plan [34].…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC

Fiste,

Gkiozos,

Charpidou

et al. 2024

Cancers

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Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality among women and men, in developed countries, despite the public health interventions including tobacco-free campaigns, screening and early detection methods, recent therapeutic advances, and ongoing intense research on novel antineoplastic modalities. Targeting oncogenic driver mutations and immune checkpoint inhibition has indeed revolutionized NSCLC treatment, yet there still remains the unmet need for robust and standardized predictive biomarkers to accurately inform clinical decisions. Artificial intelligence (AI) represents the computer-based science concerned with large datasets for complex problem-solving. Its concept has brought a paradigm shift in oncology considering its immense potential for improved diagnosis, treatment guidance, and prognosis. In this review, we present the current state of AI-driven applications on NSCLC management, with a particular focus on radiomics and pathomics, and critically discuss both the existing limitations and future directions in this field. The thoracic oncology community should not be discouraged by the likely long road of AI implementation into daily clinical practice, as its transformative impact on personalized treatment approaches is undeniable.

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“…The cumulative energies of the AAI/DS, Center for Informatics, TGen, as well as the efforts of independent COH investigators have helped create a rich resource of AI expertise and maintain a robust portfolio of AI research. Examples of other initiatives at COHthat illustrate the depth and breadth of the AI Silecosystem include the use of AI autosegmentation for patients pending bone marrow transplant irradiation [344][345][346], AI-assisted oncologic drug design [347], expert critical review of clinical AI models [348], AI-based platforms for the evaluation and treatment of lung [349] and breast cancers [350], machine learning enabled pre-surgery physical status scoring [351] and AI-assisted irradiation dose estimation [352].…”

Section: Software Resourcesmentioning

confidence: 99%

Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise

McDonnell

2023

JCM

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Over the last 75 years, artificial intelligence has evolved from a theoretical concept and novel paradigm describing the role that computers might play in our society to a tool with which we daily engage. In this review, we describe AI in terms of its constituent elements, the synthesis of which we refer to as the AI Silecosystem. Herein, we provide an historical perspective of the evolution of the AI Silecosystem, conceptualized and summarized as a Kuhnian paradigm. This manuscript focuses on the role that the AI Silecosystem plays in oncology and its emerging importance in the care of the community oncology patient. We observe that this important role arises out of a unique alliance between the academic oncology enterprise and community oncology practices. We provide evidence of this alliance by illustrating the practical establishment of the AI Silecosystem at the City of Hope Comprehensive Cancer Center and its team utilization by community oncology providers.

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Integration of artificial intelligence in lung cancer: Rise of the machine

Cited by 24 publications

References 95 publications

Artificial Intelligence and Anticancer Drug Development—Keep a Cool Head

Artificial Intelligence and Anticancer Drug Development—Keep a Cool Head

Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC

Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise

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