P2.16-22 Predictive Analytic of Survival Using a Neural Network in a Real World Cohort of Advanced Non Small Cell Lung Cancer Patients

Pino, Luis Eduardo; Ospina, A. Salazar; Triana, Iván; Pino, Jesus; Camelo, Clara Gontijo; Mejía, Juan Gutiérrez; Pena, Damaris

doi:10.1016/j.jtho.2019.08.1889

Cited by 2 publications

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“…-Algorithmic prediction will provide prevention of diseases and the mitigation of the burden of the disease, which is the fi nal objective of the intelligent/predictive epidemiology [2].…”

Section: Some Examples Includementioning

confidence: 99%

“…MAIA is for now a patient and physician experience improvement, but the real impact will be in the data acquisition and harmonization for advanced analytics. The fi nal scope of MAIA HIP will be a blockchain for cancer in low and middle income countries" [2]. DEI is determined by the following components for its correct applicability and understanding:…”

Section: Introductionmentioning

confidence: 99%

“…A Neural Network in a Real World Cohort of Advanced Non-Small Cell Lung Cancer Patients. Take from[2].…”

mentioning

confidence: 99%

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Digital epidemiology of innovation

Triana¹,

Pino²,

Cruz³

2021

Open J Trop Med

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Bio and infotech revolution including data management are global tendencies that have a relevant impact on healthcare. Concepts such as Big Data, Data Science and Machine Learning are now topics of interest within medical literature. All of them are encompassed in what recently is named as digital epidemiology. The purpose of this article is to propose our defi nition of digital epidemiology with the inclusion of a further aspect: Innovation. It means Digital Epidemiology of Innovation (DEI) and show the importance of this new branch of epidemiology for the management and control of diseases. In this sense, we will describe all characteristics concerning to the topic, current uses within medical practice, application for the future and applicability of DEI as conclusion.

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“…-Algorithmic prediction will provide prevention of diseases and the mitigation of the burden of the disease, which is the fi nal objective of the intelligent/predictive epidemiology [2].…”

Section: Some Examples Includementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Digital epidemiology of innovation

Triana¹,

Pino²,

Cruz³

2021

Open J Trop Med

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Digital Epidemiology of Innovation (Preprint)

Triana¹,

Pino²,

Rubio³

2021

Preprint

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UNSTRUCTURED Bio and infotech revolution including data management are global tendencies that have a relevant impact on healthcare. Concepts such as Big Data, Data Science and Machine Learning are now topics of interest within medical literature. All of them are encompassed in what recently is named as digital epidemiology. The purpose of this article is to propose our definition of digital epidemiology with the inclusion of a further aspect: Innovation. It means Digital Epidemiology of Innovation (DEI) and show the importance of this new branch of epidemiology for the management and control of diseases. In this sense, we will describe all characteristics concerning to the topic, current uses within medical practice, application for the future and applicability of DEI as conclusion.

show abstract

P2.16-22 Predictive Analytic of Survival Using a Neural Network in a Real World Cohort of Advanced Non Small Cell Lung Cancer Patients

Cited by 2 publications

References 0 publications

Digital epidemiology of innovation

Digital epidemiology of innovation

Digital Epidemiology of Innovation (Preprint)

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