Altug Akay

Advances in Smartphone-Based Point-of-Care Diagnostics

Point-of-care (POC) diagnostics is playing an increasingly important role in public health, environmental monitoring, and food safety analysis. Smartphones, alone or in conjunction with add-on devices, have shown great capability of data collection, analysis, display, and transmission, making them popular in POC diagnostics. In this article, the state-of-the-art advances in smartphone-based POC diagnostic technologies and their applications in the past few years are outlined, ranging from in vivo tests that use smartphones built-in/external sensors to detect biological signals to in vitro tests that involves complicated biochemical reactions. Novel techniques are illustrated by a number of attractive examples, followed by a brief discussion of the smartphones role in telemedicine. The challenges and perspectives of smartphone-based POC diagnostics are also provided.

A Novel Data-Mining Approach Leveraging Social Media to Monitor Consumer Opinion of Sitagliptin

A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of users clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members. These findings can open new avenues of research into rapid data collection, feedback, and analysis that can enable improved outcomes and solutions for public health and important feedback for the manufacturer.

A novel data-mining approach leveraging social media to monitor and respond to outcomes of diabetes drugs and treatment

A novel data-mining method was developed to gauge the experiences of medical devices and drugs by patients with diabetes mellitus. Self-organizing maps were used to analyze forum posts numerically to better understand user opinion of medical devices and drugs. The end-result is a word list compilation that correlates certain positive and negative word cluster groups with medical drugs and devices. The implication of this novel data-mining method could open new avenues of research into rapid data collection, feedback, and analysis that would enable improved outcomes and solutions for public health.

A Data-Mining Approach for Investigating Social and Economic Geographical Dynamics of

beta-Thalassemia is an anemic genetic disorder that remains a major global health issue, especially in the globalized era where public health, economics, and education are tightly interwoven. Previous studies have examined the diseases rate and heredity. This study analyzed beta-thalassemias socioeconomic geography and how it affects the afflicted population. We processed survey data and performed data mining using self-organizing maps to identify underlying data structure. We hypothesized that certain variables mark subgroups within the affected population and we aimed at identifying these subgroups and used a correlation-based measure to assess the variables importance to the subgroups distinction. The populations education level was one of the major factors that divided it into different subgroups. Our study showed that recurring patterns of specific variables separated the affected population into disparate subgroups based on their response to questionnaires. Future studies can use such tools to delve deeper into how other variables (e.g. socioeconomic and genomic) can identify subgroups within larger affected populations.

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A novel data-mining method was developed to gauge the experiences of the diabetes mellitus drug Januvia. Self-organizing maps were used to analyze forum posts numerically to infer user opinion of drug Januvia. Graph theory was used to discover influential users. The result is a word list compilation correlating positive and negative word cluster groups and a web of influential users on Januvia. The implications could open new research avenues into rapid data collection, feedback, and analysis that would enable improved solutions for public health.

-Thalassemia's Spread

A novel data-mining method was developed to gauge the experiences of the oncology drug Tarceva. Self-organizing maps were used to analyze forum posts numerically to infer user opinion of drug Tarceva. The result is a word list compilation correlating positive and negative word cluster groups and a web of influential users on Tarceva. The implica-tions could open new research avenues into rapid data collec-tion, feedback, and analysis that would enable improved solu-tions for public health.

A novel data-mining platform leveraging social media to monitor outcomes of Januvia

P-Thalassemia is an anemic genetic disorder that continues to affect between 3-10% of populations residing every country in the Mediterranean, Maghreb, Southwest, South, and Southeast Asia. While many studies surrounding 8-thalassemia concentrated either on genetic or social applications, we applied a joint method to explain J-Thalassemia’s spread rate. The data generated from interviews and questionnaires were converted into numerical values to ascertain what variables contribute to R-thalassemia’s spread rate. We hypothesized that a strong correlation among certain variables (limited education, information availability, and neighborhood prevention programs, financial insolvency, and treatment affordability) exists, Using a self-organizing map (SOM) in the analysis (due to large data content) allowed us to group the data into five regions corresponding to dominant variables responsible for 8-thalassemia’s spread. After studying the mapped data and relevant variables, we concluded that education correlated to 8-thalassemia’s spread rate. Education affected other variables that contributed to 8-thalassemia’s spread. We concluded that a combined aggressive education/prevention and treatment programs can prevent 8-thalassemia’s spread.