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1.
Appl Stoch Models Bus Ind ; 35(2): 376-393, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-34135693

RESUMEN

We propose a new method to find modes based on active information. We develop an algorithm called active information mode hunting (AIMH) that, when applied to the whole space, will say whether there are any modes present and where they are. We show AIMH is consistent and, given that information increases where probability decreases, it helps to overcome issues with the curse of dimensionality. The AIMH also reduces the dimensionality with no resource to principal components. We illustrate the method in three ways: with a theoretical example (showing how it performs better than other mode hunting strategies), a real dataset business application, and a simulation.

2.
Int J Telemed Appl ; 2018: 1496941, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-29785181

RESUMEN

BACKGROUND: The use of mobile applications in dermatology to support remote diagnosis is gaining acceptance, particularly in rural areas, where dermatology services are commonly managed by healthcare personnel with no specialty training. Moreover, ontologies-sets of concepts that represent knowledge in a given domain-are increasingly being used to support medical diagnosis. A specific case is ONTODerm: an ontology to aid dermatological diagnosis. However, there is little information on the combined use of mobile applications and ontologies as support solutions in dermatology. OBJECTIVE: Assessing the reliability of ONTODerm as a tool to support remote dermatological diagnosis when used together with a mobile dermatological application in underprivileged areas. METHODS: A mobile application that allows characterization of skin lesions was developed, and the information about the lesions was sent to ONTODerm. An exploratory study was conducted in a remote area without access to a dermatologist. A total of 64 dermatological queries were recorded in the application and consulted with ONTODerm. Later, an experienced dermatologist evaluated the characterization and diagnosis of each query to determine the accuracy of the system. RESULTS: The results showed that the probability of obtaining a correct diagnosis was between 64.4% and 85.6% with a confidence interval of 95%. A higher accuracy rate was obtained when the skin lesion occurred on the face or when its border was categorized as poorly demarcated. CONCLUSIONS: This study demonstrates the implementation of a teledermatology strategy based on mobile applications and domain ontology-driven knowledge base to provide timely assistance to healthcare professionals. This approach was found to be pertinent in the Colombian rural context, particularly in forest regions, where dermatology specialists are not available. The results of this article do not represent a final validation of the proposed approach; they suggest how the ontology can be improved to effectively support medical staff in marginalized regions.

3.
JMIR Mhealth Uhealth ; 2(3): e38, 2014 Sep 25.
Artículo en Inglés | MEDLINE | ID: mdl-25263432

RESUMEN

BACKGROUND: Sexual risk behaviors associated with poor information on sexuality have contributed to major public health problems in the area of sexual and reproductive health in teenagers and young adults in Colombia. OBJECTIVE: To report our experience with the use of DoctorChat Mobile to provide sexual education and information among university students in Bogota, Colombia, and knowledge about the sexual risk factors detected among them. METHODS: A mobile app that allows patients to ask about sexual and reproductive health issues was developed. Sexual and reproductive risk behaviors in a sample of young adults were measured before and after the use of the app through the validated survey Family Health International (FHI) Behavioral Surveillance Survey (BSS) for Use With Adults Between 15 and 49 Years. A nonprobabilistic convenience recruitment was undertaken through the study´s webpage. After completing the first survey, participants were allowed to download and use the app for a 6-month period (intervention), followed by completion of the same survey once again. For the inferential analysis, data was divided into 3 groups (dichotomous data, discrete quantitative data, and ordinal data) to compare the results of the questions between the first and the second survey. The study was carried out with a sample of university students between 18 and 29 years with access to mobile phones. Participation in the study was voluntary and anonymous. RESULTS: A total of 257 subjects met the selection criteria. The preintervention survey was answered by 232 subjects, and 127 of them fully answered the postintervention survey. In total, 54.3% (69/127) of the subjects completed the survey but did not use the app, leaving an effective population of 58 subjects for analysis. Of these subjects, 53% (31/58) were women and 47% (27/58) were men. The mean age was 21 years, ranging between 18 and 29 years. The differences between the answers from both surveys were not statistically significant. The main sexual risk behaviors identified in the population were homosexual intercourse, nonuse of condoms, sexual intercourse with nonregular and commercial partners, the use of psychoactive substances, and lack of knowledge on symptoms of sexually transmitted diseases and HIV transmission. CONCLUSIONS: Although there were no differences between the pre- and postintervention results, the study revealed different risk behaviors among the participating subjects. These findings highlight the importance of promoting high-impact educational strategies on this matter and the importance of providing teenagers and young adults with easily accessible tools with reliable health information, regardless of their socioeconomic status.

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