Evidence From Web-Based Dietary Search Patterns to the Role of B12 Deficiency in Non-Specific Chronic Pain: A Large-Scale Observational Study

ACM Trans. Comput. Healthcare

2020

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Studies have shown that the traces people leave when browsing the internet may indicate the onset of diseases such as cancer. Here we show that the adaptive engines of advertising systems in conjunction with clinically verified questionnaires can be used to identify people who are suspected of having one of three types of solid tumor cancers.In the first study, 308 people were recruited through ads shown on the Bing search engine to complete a clinically verified risk questionnaire. A classifier trained to predict questionnaire response using only past queries on Bing reached an Area Under the Curve of 0.64 for all three cancer types, verifying that past searches could be used to identify people with suspected cancer.The second study was conducted using the Google ads system in the same configuration as in the first study. However, in this study the ads system was set to automatically learn to identify people with suspected cancer. A total of 70,586 people were shown the ads, and 6,484 clicked and were referred to complete the clinical questionnaires. People from countries with higher Internet access and lower life expectancy tended to click more on the ads. Over time the advertisement system learned to identify people who were likely to have symptoms consistent with suspected cancer, such that the percentage of people completing the questionnaires and found to have suspected cancer reached approximately 11% at the end of the experiment.These results demonstrate the utility of using search engine queries to screen for possible cancer and the application of modern advertising systems to help identify people who are likely suffering from serious medical conditions. This is especially true in countries where medical services are less developed.

Section: Introductionmentioning

confidence: 99%

Screening for Cancer Using a Learning Internet Advertising System

ACM Trans. Comput. Healthcare

2020

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“…The richness of search engine queries, reflecting a broad range of human behaviors, has led researchers analyze these data to learn about aspects of health which are difficult to study in other ways [19]. These studies begun from an examination of broad aspects of public health, e.g., the prevalence of influenza in a population [11] and the effect of dietary deficiencies on certain chronic pains [3]. More intriguingly, recent work has demonstrated that insights pertaining to individuals can be found their queries.…”

Section: Introductionmentioning

confidence: 99%

Demographic differences in search engine use with implications for cohort selection

2019

Inf Retrieval J

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The correlation between the demographics of users and the text they write has been investigated through literary texts and, more recently, social media. However, differences pertaining to language use in search engines has not been thoroughly analyzed, especially for age and gender differences. Such differences are important especially due to the growing use of search engine data in the study of human health, where queries are used to identify patient populations.Using data from multiple general-purpose Internet search engines gathered over a period of one month we investigate the correlation between demography (age, gender, and income) and the text of queries submitted to search engines.Our results show that females and younger people use longer queries. This difference is such that females make approximately 25% more queries with 10 or more words. In the case of queries which identify users as having specific medical conditions we find that females make 50% more queries than expected, and that this results in patient cohorts which are highly skewed in gender and age, compared to known gender balance.Our results indicate that studies where demographic representation is important, such as in the study of health aspect of users or when search engines are evaluated for fairness, care should be taken in the selection of search engine data so as to create a representative dataset.

“…Recipe searches provide a representative sample of the dietary consumption of individuals [18]. Therefore, to evaluate the changes in diet made by people with CRQs, we followed the methodology used previously [18] to identify queries for recipes and map them to ingredients therein.…”

Section: Methodsmentioning

confidence: 99%

Symptoms Prompting Interest in Celiac Disease and the Gluten-Free Diet: Analysis of Internet Search Term Data

Lebwohl

2019

J Med Internet Res

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Background Celiac disease, a common immune-based disease triggered by gluten, has diverse clinical manifestations, and the relative distribution of symptoms leading to diagnosis has not been well characterized in the population. Objective This study aimed to use search engine data to identify a set of symptoms and conditions that would identify individuals at elevated likelihood of a subsequent celiac disease diagnosis. We also measured the relative prominence of these search terms before versus after a search related to celiac disease. Methods We extracted English-language queries submitted to the Bing search engine in the United States and identified those who submitted a new celiac-related query during a 1-month period, without any celiac-related queries in the preceding 9 months. We compared the ratio between the number of times that each symptom or condition was asked in the 14 days preceding the first celiac-related query of each person and the number of searches for that same symptom or condition in the 14 days after the celiac-related query. Results We identified 90,142 users who made a celiac-related query, of whom 6528 (7%) exhibited sustained interest, defined as making a query on more than 1 day. Though a variety of symptoms and associated conditions were also queried before a celiac-related query, the maximum area under the receiver operating characteristic curve was 0.53. The symptom most likely to be queried more before than after a celiac-related query was diarrhea (query ratio [QR] 1.28). Extraintestinal symptoms queried before a celiac disease query included headache (QR 1.26), anxiety (QR 1.10), depression (QR 1.03), and attention-deficit hyperactivity disorder (QR 1.64). Conclusions We found an increase in antecedent searches for symptoms known to be associated with celiac disease, a rise in searches for depression and anxiety, and an increase in symptoms that are associated with celiac disease but may not be reported to health care providers. The protean clinical manifestations of celiac disease are reflected in the diffuse nature of antecedent internet queries of those interested in celiac disease, underscoring the challenge of effective case-finding strategies.