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[A Public Database of biomechanical parameters of gait in young Chileans].
Rev Med Chil
May 2024
Escuela de Kinesiología, Universidad de los Andes, Santiago, Chile.
Unlabelled: Biomechanical analysis of gait encompasses the measurement of spatiotemporal (STVs), kinematics, and kinetics variables. The behavior of these variables can provide clinicians and researchers with insights into the normality or alteration of this motor act across different populations. However, there is a lack of reference data for the Chilean population.
View Article and Find Full Text PDFCase report: Additional grounds for tighter regulation? A case series of five women with zolpidem dependence from a Brazilian women-specific substance use disorder outpatient service.
Front Psychiatry
December 2024
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (FMUSP), Instituto de Psiquiatria, São Paulo, Brazil.
Objective: This study presents a case series of five women with zolpidem dependence treated at the Drug Dependent Women Treatment Center (PROMUD), one of the first women-specific substance use disorder outpatient services in Latin America.
Methods: This was an retrospective review of medical records of patients with a diagnosis of zolpidem dependence at the Institute of Psychiatry of Clinics Hospital of University of São Paulo between December 2021 and December 2023. Description of the cases followed the Case Report Statement, Checklist and Guidelines (CARE).
Logical reasoning for human activity recognition based on multisource data from wearable device.
Sci Rep
January 2025
Dr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & Technology, Tathawade, Pune, India.
Article Synopsis
- Smart wearables are essential for health monitoring and assisting the elderly or individuals with disabilities, but current machine learning methods face high resource demands and limited scalability.
- This research introduces a new behavior detection approach that combines multi-source sensing with logical reasoning, aiming to streamline the process of behavior recognition.
- The developed system achieves over 90% accuracy in recognizing 11 daily activities while significantly reducing the need for extensive training data compared to traditional machine learning methods.
Communicating evidence-based information on the effects of health interventions to various types of recipients - a qualitative study on the perception of formats of information among lay and professional audiences.
Ann Agric Environ Med
December 2024
Department of Hygiene and Dietetics, Jagiellonian University Medical College, Krakow, Poland.
Introduction And Objective: Considering the complexity of medical discourse, the enormous amount of information, including fake news, it becomes increasingly challenging to develop health literacy among the general population and to ensure efficient communication of scientific findings on the effects of health interventions to various types of recipients. We aimed to gain an in-depth understanding of how the various types of audiences perceive various formats for presenting data from Cochrane systematic reviews (SRs).
Material And Methods: We conducted focus group interviews with university employees, students, pharmacists, patients, caregivers, physicians, and nurses.
Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assay.
Environ Mol Mutagen
December 2024
Research and Development, Preclinical Safety, Sanofi, Industriepark Hoechst, Frankfurt am Main, Germany.
Genotoxicity is a critical determinant for assessing the safety of pharmaceutical drugs, their metabolites, and impurities. Among genotoxicity tests, mechanistic assays such as the MultiFlow® DNA damage assay (MFA) allows the investigations on mode of action (MoA) of DNA damage through four mechanistic markers recorded at two time points. Previous studies have shown that machine learning (ML) can enhance precision on classifying the MoA of genotoxicants.
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