Browsing by Author "Taramasco, Carla"
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- ItemDifferential Effects of a Telemonitoring Platform in the Development of Chemotherapy-Associated Toxicity: A Randomized Trial Protocol(2024) Martínez, Felipe; Taramasco, Carla; Espinoza Sepúlveda, Manuel Antonio; Acevedo, Johanna; Goic Boroevic, Carolina; Nervi Nattero, BrunoChemotherapy requires careful monitoring, but traditional follow-up approaches face significant challenges that were highlighted by the COVID-19 pandemic. Hence, exploration into telemonitoring as an alternative emerged. The objective is to assess the impact of a telemonitoring platform that provides clinical data to physicians overseeing solid tumor patients, aiming to enhance the care experience. The methodology outlines a parallel-group randomized clinical trial involving recently diagnosed patients with solid carcinomas preparing for curative intent chemotherapy. Eligible adult patients diagnosed with specific carcinoma types and proficient in Spanish, possessing smartphones, will be invited to participate. They will be randomized using concealed allocation sequences into two groups: one utilizing a specialized smartphone application called Contigo for monitoring chemotherapy toxicity symptoms and accessing educational content, while the other receives standard care. Primary outcome assessment involves patient experience during chemotherapy using a standardized questionnaire. Secondary outcomes include evaluating severe chemotherapy-associated toxicity, assessing quality of life, and determining user satisfaction with the application. The research will adhere to intention-to-treat principles. This study has been registered at ClinicalTrials.gov (NCT06077123)
- ItemMachine learning analysis of a Chilean breast cancer registry(2021) Acevedo, Francisco; Causa, Leonardo; Bravo, Sebastián; García, Pablo; Cuevas, Ricardo; Bravo, Maria Loreto; Avellaira, Carla; Muñiz, Sabrina; Petric, Militza; Martinez, Raúl; Guerra, Constanza; Navarro, Marisel; Taramasco, Carla; Sanchez, CesarIn recent years, artificial intelligence (AI) and machine learning (a form of AI) have offered valuable tools for medicine by applying and training algorithms in order to make predictions. Herein, we applied a machine learning algorithm to analyze data from a >20 year breast cancer (BC) registry elaborated in two Chilean health institutions (a public hospital and a private center) that includes a total of 4838 patients and their basic clinicalpathological characteristics. Preliminary results suggest that this cohort of patients can be subdivided into five clusters according to key variables that also correlate with overall survival and disease-free survival rates. To our knowledge this is the first Latin American report of its kind. Our laboratory is currently expanding these analyses.