Patricia Ordóñez

University of Puerto Rico at Rio Piedras | UPR-RP · Department of Computer Science

In-person undergraduate research experiences (UREs) promote students’ integration into careers in life science research. In 2020, the COVID-19 pandemic prompted institutions hosting summer URE programs to offer them remotely, raising questions about whether undergraduates who participate in remote research can experience scientific integration and...

In-person undergraduate research experiences (UREs) promote students' integration into careers in life science research. In 2020, the COVID-19 pandemic prompted institutions hosting summer URE programs to offer them remotely, raising questions about whether undergraduates who participate in remote research can experience scientific integration. To...

The COVID-19 pandemic shut down undergraduate research programs across the United States. A group of 23 colleges, universities, and research institutes hosted remote undergraduate research programs in the life sciences during Summer 2020. Given the unprecedented offering of remote programs, we carried out a study to describe and evaluate them. Usin...

The bee family Halictidae is considered to be an optimal model for the study of social evolution due to its remarkable range of social behaviors. Past studies in circadian rhythms suggest that social species may express more diversity in circadian behaviors than solitary species. However, these previous studies did not make appropriate taxonomic co...

The COVID-19 pandemic shut down undergraduate research programs across the U.S. Twenty-three sites offered remote undergraduate research programs in the life sciences during summer 2020. Given the unprecedented offering of remote research experiences, we carried out a study to describe and evaluate these programs. Using structured templates, we doc...

Objective Information gaps that accompany hurricanes and floods limit researchers’ ability to determine the impact of disasters on population health. Defining key use cases for sharing complex disaster data with research communities and facilitators, and barriers to doing so are key to promoting population health research for disaster recovery. Ma...

With the growth of data in a plethora of fields ranging from agriculture to medicine to finance, data science is quickly becoming one of the most in demand professional careers of the decade. However, only a handful of minority serving institutions in the US have a course much less a formal program or certification track in data science. This paper...

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale...

Exploring Computer Science (ECS) [1] spawned from the need to provide access to Computer Science to everyone in the US. The success and commitment to equity and diversity of the ECS curriculum in Latina/o communities inspired an interdisciplinary group of educators from the University of Puerto Rico to tackle the lack of K-12 CSE on the island. Thi...

This special session is intended for people who are curious about integrating Humanitarian Free and Open Source Software (HFOSS) into their courses and involving students in HFOSS projects. HFOSS participation provides an excellent vehicle to introduce students to computing for social good while also giving them experience with real-world software...

This paper intends to share both the experience of teachers and document the research of the design, implementation, and evaluation of a massive open online course (MOOC). The primary purpose of the MOOC was to do outreach and build community to interest teachers from any discipline in Puerto Rico to incorporate Computational Thinking (CT) into the...

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institu...

OBJECTIVES/SPECIFIC AIMS: To learn the edit distance costs of a symbolic univariate time series representation through a stochastic finite-state transducer to predict patient outcomes in intensive care units. METHODS/STUDY POPULATION: High frequency data of patients in intensive care units were used as a data set. The nearest neighbor method with e...

In the spirit of “hack-a-thons” that build solutions, we leveraged resources from NSF Alliance for Graduate Education and the Professoriate (AGEP), ADVANCE, and Louis Stokes Alliance for Minority Participation Bridge to the Doctorate programs to co-develop “hacking diversity in STEM” events for underrepresented groups (URG) in STEM. These activitie...

This paper describes the experience of the first author with the Point-and-Click Interface of the OnScreenDualScribe, created by the last author. The new interface is an innovative extension to the previous interface which required the use of the DualPad. The main differences between the two interfaces are highlighted. The user took several writing...

The high frequency data in intensive care unit is flashed on a screen for a few seconds and never used again. However, this data can be used by machine learning and data mining techniques to predict patient outcomes. Learning finite-state transducers (FSTs) have been widely used in problems where sequences need to be manipulated and insertions, del...

Speech recognition software technology provides people with limited hand mobility or visual impairments the opportunity to work with computers through an alternative approach. However, when it comes to programming, voice recognition systems leave much to be desired. To tackle this problem, we have developed a generic vocabulary and grammar to help...

The present invention consists of a modification and a new method of today's art 12 lead resting electrocardiogram The modifications include: Elimination of connecting means to record today's art Leads; connecting means to connect a common positive electrode, placed on the left leg, to all the positive terminals of the electrocardiographic amplifie...

Programming is an arduous task for individuals with motor impairments who rely on independent tools to interact with their digital environment. Providing a bimodal Integrated Development Environment is key to tackling a program's complex syntax and to improving the programming interface. This project is an effort to facilitate the interaction betwe...

In this paper we examine two novel multivariate time se-ries representations to classify physiological data of differ-ent lengths, Multivariate Bag-of-Patterns and Stacked Bags-of-Patterns. We also borrow techniques from the natural language processing and text mining (e.g., term frequency and inverse document frequency) to improve classification a...

Existing visualizations in the neonatal intensive care unit (NICU) frequently obscure important trends in clinical data presented to the clinician in tabular displays or stacked univariate plots of variables as a function of time. Scales and alarm limits in clinical displays are based on data that is typical for adults (i.e., adult “norm data”), re...

In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that examine the state or health of an entity. Multivariate Bag-of-Patterns and Stacked Bags of-Patterns improve on their univariate counter...

In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that examine the state or health of an entity. Multivariate Bag-of-Patterns and Stacked Bags of-Patterns improve on their univariate counter...

Identifying specific needs for informatics solution in Low and Middle Income Countries (LMIC) is a critical step to disseminate the benefits of advanced information technology on a global scale. We set out an exploratory visit to a medical a school and its affiliated university hospital to describe how information technology could improve their dai...

Current visualizations of electronic medical data in the Intensive Care Unit (ICU) consist of stacked univariate plots of variables over time and a tabular display of the current numeric values for the corresponding variables and occasionally an alarm limit. The value of information is dependent upon knowledge of historic values to determine a chan...

Efficient unsupervised algorithms for the detection of patterns in time series data, often called motifs, have been used in many applications, such as identifying words in different languages, detecting anomalies in ECG readings, and finding similarities between images. We present a process that creates a personalized multivariate time series repre...

The age of technology has changed the way that surgeons are being trained. Traditional methodologies for training can include lecturing, shadowing, apprenticing, and developing skills within live clinical situations. Computerized tools which simulate surgical procedures and/or experiences can allow for "virtual" experiences to enhance the tradition...

Text analytics is becoming an increasingly important tool used in biomedical research. While advances continue to be made in the core algorithms for entity identification and relation extraction, a need for practical applications of these technologies arises. We developed a system that allows users to explore the US Patent corpus using molecular in...

We aim to create a multivariate temporal representation of electronic medical data which automates the personalization of baselines and thresholds based on a patient's history. Visualizations based on the representation emphasize the rate of change in variables and assist providers in analyzing the data from a multivariate perspective. A novel simi...