Anisah Hayaminnah Alonto

Dr. Anisah Hayaminnah Alonto

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 January 2022 in Neurological Sciences
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Journal Article
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AAAnisah Hayaminnah Alonto
Anisah Hayaminnah Alonto
Roland Dominic G. JamoraRoland Dominic G. Jamora
Roland Dominic G. Jamora
CLCarl Froilan D. Leochico
Carl Froilan D. Leochico
AEAdrian Espiritu
Adrian Espiritu

30 November 2023 in Parkinsonism & Related Disorders
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Journal Article
Closed access
AAAnisah Hayaminnah Alonto
Anisah Hayaminnah Alonto
Roland Dominic G. JamoraRoland Dominic G. Jamora
Roland Dominic G. Jamora

1 December 2021 in Current Problems in Cancer
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Journal Article
Closed access
AAAnisah Hayaminnah Alonto
Anisah Hayaminnah Alonto
MMMark Willy L. Mondia
Mark Willy L. Mondia
CPCyril Jonas M. Planilla
Cyril Jonas M. Planilla
MMMarvin Jonne Mendoza
Marvin Jonne Mendoza
SUSheen C. Urquiza
Sheen C. Urquiza
MBMarjorie Anne C. Bagnas
Marjorie Anne C. Bagnas

AAAnisah Hayaminnah Alonto
Anisah Hayaminnah Alonto
Almira Doreen Abigai AporAlmira Doreen Abigai Apor
Almira Doreen Abigai Apor
Roland Dominic G. JamoraRoland Dominic G. Jamora
Roland Dominic G. Jamora
Due to the real-time acquisition of big data from the Internet, analysis of Google queries is now recognized as a valuable tool to explore and predict human behavior and interests. It was suggested that online data can be correlated with actual health data. Although the data are not structured nor systematic, the huge data from search engines can easily identify trends concerning diseases and other health concepts from a population perspective. Moreover, Internet data with the use of web search advertising nowadays may not only reveal the interest of the general population but also of the healthcare industry as reflected by the bid prices in search terms for medications. We aimed to compare the interests of the general population using monthly search volumes from Google and the healthcare industry using bid prices in web searches. Data used in this study were obtained from the Google Ads Application Programming Interface (API). This study evaluated the population’s interest in neurological disorders by using search volumes related to neurology, either disease diagnosis or medications. Bid values generated in API were used as a proxy for the interests of the healthcare industry. Spearman’s rank-order correlation was performed between search volumes and bid prices to determine significance. Among the neurologic diseases listed, the most searched were attention deficit hyperactivity disorder, migraine, and Alzheimer’s disease. The most commonly searched drugs were oral antihypertensives (amlodipine, losartan, carvedilol), lipid-lowering agents (atorvastatin, simvastatin, rosuvastatin), and antiplatelets (acetylsalicylic acid, clopidogrel). The other most searched drugs were analgesics such as acetaminophen, tramadol, diclofenac, and morphine. The correlational analysis did not reveal a statistically significant correlation between search volume and bid price for both neurologic diseases and medications. Web searches may reflect the interest of the general population and the healthcare industry. However, there was disagreement in the search interests of the general population and the scientific community, including the pharmaceutical industry. Further studies are necessary in order to align these interests for the common benefit of all stakeholders.

3 December 2024 in Current Problems in Cancer
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Journal Article
Closed access
MMMark Willy L. Mondia
Mark Willy L. Mondia
AAAnisah Hayaminnah Alonto
Anisah Hayaminnah Alonto
NPNicole Girlyn T. Pang
Nicole Girlyn T. Pang
FRFrancis Manuel L. Resma
Francis Manuel L. Resma
AMAl Joseph R. Molina
Al Joseph R. Molina
JBJulette Marie F. Batara
Julette Marie F. Batara