An optimized support vector machine for lung cancer classification system.

Introduction: Lung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early categorization is essential. The goal of thisresearch is to enhance machine learning to increase the precision and quality of lung cancer classification.

Exploring the versatility of as a model organism in biomedical research: a comprehensive review.

is a highly versatile model organism that has profoundly advanced our understanding of human diseases. With more than 60% of its genes having human homologs, provides an invaluable system for modelling a wide range of pathologies, including neurodegenerative disorders, cancer, metabolic diseases, as well as cardiac and muscular conditions. This review highlights key developments in utilizing for disease modelling, emphasizing the genetic tools that have transformed research in this field.

Mechanical and chemical characterization of biochar-reinforced polystyrene composites.

This study investigates the chemical interactions and mechanical characteristics of composites made of polystyrene reinforced with biochar. Polystyrene-based resin (PBR) was combined with plantain peel-derived biochar in different weight ratios (10%, 20%, 30%, and 40%). The Brinell hardness test, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS) were used to evaluate the properties of the composites.

Fostering Inclusivity in PM&R: A National Survey.

There is a persistent underrepresentation of women and multiple ethnic minority groups among medical school and residency applicants and trainees, particularly in Physical Medicine and Rehabilitation (PM&R). There is limited information on what causes these demographic disparities in PM&R and on strategies to increase interest in the field. To address this gap and improve early recruitment efforts, the authors conducted the first-ever national survey to gather information on pre-medical students' perceived barriers to medical school admissions, career interests, perceptions of PM&R, and strategies to increase interest in PM&R.