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McDonnell KJ. Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise. J Clin Med 2023; 12:4830. [PMID: 37510945 PMCID: PMC10381436 DOI: 10.3390/jcm12144830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
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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Affiliation(s)
- Kevin J McDonnell
- Center for Precision Medicine, Department of Medical Oncology & Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
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Himawan A, Vora LK, Permana AD, Sudir S, Nurdin AR, Nislawati R, Hasyim R, Scott CJ, Donnelly RF. Where Microneedle Meets Biomarkers: Futuristic Application for Diagnosing and Monitoring Localized External Organ Diseases. Adv Healthc Mater 2023; 12:e2202066. [PMID: 36414019 DOI: 10.1002/adhm.202202066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 11/03/2022] [Indexed: 11/24/2022]
Abstract
Extracellular tissue fluids are interesting biomatrices that have recently attracted scientists' interest. Many significant biomarkers for localized external organ diseases have been isolated from this biofluid. In the diagnostic and disease monitoring context, measuring biochemical entities from the fluids surrounding the diseased tissues may give more important clinical value than measuring them at a systemic level. Despite all these facts, pushing tissue fluid-based diagnosis and monitoring forward to clinical settings faces one major problem: its accessibility. Most extracellular tissue fluid, such as interstitial fluid (ISF), is abundant but hard to collect, and the currently available technologies are invasive and expensive. This is where novel microneedle technology can help tackle this significant obstacle. The ability of microneedle technology to minimally invasively access tissue fluid-containing biomarkers will enable ISF and other tissue fluid utilization in the clinical diagnosis and monitoring of localized diseases. This review attempts to present the current pursuit of the application of microneedle systems as a diagnostic and monitoring platform, along with the recent progress of biomarker detection in diagnosing and monitoring localized external organ diseases. Then, the potential use of various microneedles in future clinical diagnostics and monitoring of localized diseases is discussed by presenting the currently studied cases.
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Affiliation(s)
- Achmad Himawan
- School of Pharmacy, Queen's University Belfast, Belfast, BT97BL, UK.,Department of Pharmaceutical Science and Technology, Faculty of Pharmacy, Hasanuddin University, Makassar, 90245, Indonesia
| | | | - Andi Dian Permana
- Department of Pharmaceutical Science and Technology, Faculty of Pharmacy, Hasanuddin University, Makassar, 90245, Indonesia
| | - Sumarheni Sudir
- Department of Pharmacy, Faculty of Pharmacy, Hasanuddin University, Makassar, 90245, Indonesia
| | - Airin R Nurdin
- Department of Dermatology and Venereology, Faculty of Medicine, Hasanuddin University, Makassar, 90245, Indonesia.,Hasanuddin University Hospital, Hasanuddin University, Makassar, 90245, Indonesia
| | - Ririn Nislawati
- Hasanuddin University Hospital, Hasanuddin University, Makassar, 90245, Indonesia.,Department of Ophthalmology, Faculty of Medicine, Hasanuddin University, Makassar, 90245, Indonesia
| | - Rafikah Hasyim
- Department of Oral Biology, Faculty of Dentistry, Hasanuddin University, Makassar, 90245, Indonesia
| | - Christopher J Scott
- Patrick G Johnson Centre for Cancer Research, Queen's University Belfast, Belfast, BT97BL, UK
| | - Ryan F Donnelly
- School of Pharmacy, Queen's University Belfast, Belfast, BT97BL, UK
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Arano-Martinez JA, Martínez-González CL, Salazar MI, Torres-Torres C. A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning. BIOSENSORS 2022; 12:710. [PMID: 36140093 PMCID: PMC9496380 DOI: 10.3390/bios12090710] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/22/2022] [Accepted: 08/25/2022] [Indexed: 11/25/2022]
Abstract
The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.
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Affiliation(s)
- Jose Alberto Arano-Martinez
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Ingeniería Mecánica y Eléctrica, Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Claudia Lizbeth Martínez-González
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Ingeniería Mecánica y Eléctrica, Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Ma Isabel Salazar
- Departamento de Microbiología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City 11340, Mexico
| | - Carlos Torres-Torres
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Ingeniería Mecánica y Eléctrica, Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City 07738, Mexico
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