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Publicación
Temporal distribution of schedule-induced behavior depends on the essential value of the reinforcer
(Wiley, 2025) Martínez Herrada, Antonio; Pellón Suárez de Puga, Ricardo; López Tolsa Gómez, Gabriela Eugenia
The development of schedule-induced drinking depends on different variables affecting the food delivered at the end of the interfood interval. There are mixed results concerning the effects of varying magnitude and/or preference of different reinforcers in the development of schedule-induced drinking, with some studies showing higher levels and other studies showing lower levels of drinking. The purpose of this study was to observe how differences in preference for a flavor of equally nutritious food pellets influence the development and maintenance of schedule-induced drinking. Using the operant demand framework, four flavors of food pellets were compared to form two groups: one in which subjects would receive their most preferred flavor and another in which subjects would receive their least preferred flavor. In general, licking rates were lower and magazine-entering rates were higher when the preferred flavor was delivered regardless of the fixed-time schedule used. It is suggested that the value of the reinforcer has a larger influence on the immediately preceding behaviors, which will determine the distribution of competing responses in the interreinforcement intervals. These results are relevant to developing public policies that manipulate the taste of healthy food to increase its consumption.
Publicación
Early diagnosis of HIV cases by means of text mining and machine learning models on clinical notes
(ELSEVIER, 2024) Morales Sánchez, Rodrigo; Montalvo Herranz, Soto; Riaño Martínez, Adrián; Martínez Unanue, Raquel; Velasco Arribas, Maria; https://orcid.org/0000-0001-8158-7939; https://orcid.org/0009-0004-8755-255X; https://orcid.org/0000-0001-6554-2095
Undiagnosed and untreated human immunodeficiency virus (HIV) infection increases morbidity in the HIV-positive person and allows onward transmission of the virus. Minimizing missed opportunities for HIV diagnosis when a patient visits a healthcare facility is essential in restraining the epidemic and working toward its eventual elimination. Most state-of-the-art proposals employ machine learning (ML) methods and structured data to enhance HIV diagnoses, however, there is a dearth of recent proposals utilizing unstructured textual data from Electronic Health Records (EHRs). In this work, we propose to use only the unstructured text of the clinical notes as evidence for the classification of patients as suspected or not suspected. For this purpose, we first compile a dataset of real clinical notes from a hospital with patients classified as suspects and non-suspects of having HIV. Then, we evaluate the effectiveness of two types of classification models to identify patients suspected of being infected with the virus: classical ML algorithms and two Large Language Models (LLMs) from the biomedical domain in Spanish. The results show that both LLMs outperform classical ML algorithms in the two settings we explore: one dataset version is balanced, containing an equal number of suspicious and non-suspicious patients, while the other reflects the real distribution of patients in the hospital, being unbalanced. We obtain F score figures of 94.7 with both LLMs in the unbalanced setting, while in the balance one, RoBERTa model outperforms the other one with a F score of 95.7. The findings indicate that leveraging unstructured text with LLMs in the biomedical domain yields promising outcomes in diminishing missed opportunities for HIV diagnosis. A tool based on our system could assist a doctor in deciding whether a patient in consultation should undergo a serological test.
Publicación
Efficacy of Cognitive Training in Older Adults with and without Subjective Cognitive Decline Is Associated with Inhibition Efficiency and Working Memory Span, Not with Cognitive Reserve
(Frontiers Media, 2018-02-02) López Higes, Ramón; Martín-Aragoneses, María Teresa; Rubio Valdehita, Susana; Delgado-Losada, María L.; Montejo, Pedro; Montenegro, Mercedes; Prados, José M.; Frutos Lucas, Jaisalmer; López Sanz, David
The present study explores the role of cognitive reserve, executive functions, and working memory (WM) span, as factors that might explain training outcomes in cognitive status. Eighty-one older adults voluntarily participated in the study, classified either as older adults with subjective cognitive decline or cognitively intact. Each participant underwent a neuropsychological assessment that was conducted both at baseline (entailing cognitive reserve, executive functions, WM span and depressive symptomatology measures, as well as the Mini-Mental State Exam regarding initial cognitive status), and then 6 months later, once each participant had completed the training program (Mini-Mental State Exam at the endpoint). With respect to cognitive status the training program was most beneficial for subjective cognitive decline participants with low efficiency in inhibition at baseline (explaining a 33% of Mini-Mental State Exam total variance), whereas for cognitively intact participants training gains were observed for those who presented lower WM span.