چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده | نفر چندم مقاله |
|---|---|
| زینب علیاری سرج | اول |
| عنوان | متن |
|---|---|
| خلاصه مقاله | Abstract Personalized and precision medicine aims to improve health management by leveraging diverse data sources, including genetic databases, medical records, and clinical data. It focuses on tracking healthy individuals to understand disease progression, identify patients at risk, and customize treatments based on extensive population-level data. This approach contrasts with traditional medicine by analyzing genetic profiles and biomarkers to inform individualized treatment plans. It views human diseases as complex networks rather than linear pathways, potentially revealing new connections between different diseases and leading to innovative treatments. However, challenges such as data collection, patient access, and data analysis remain significant barriers to the advancement of precision medicine. Personalized medicine focuses on treating patients as individuals throughout their healthcare journey, distinguishing it from precision medicine, which relies on big data sets and population-based approaches. Engineers play a key role in developing technologies such as micro/nanofluidics and nanotechnology for tumor cell analysis and liquid biopsies, which are enhancing diagnostic capabilities. The emergence of phenotypic personalized medicine (PPM) uses augmented AI to optimize drug therapies based on patient-specific phenotypes, and pilot trials are underway for various conditions. In addition, personal monitoring technologies, including wearables and AI-based drug selection, are advancing personalized medicine. As these technologies evolve and data quality improves, the potential for more tailored medical interventions increases, moving away from the traditional one-size-fits-all approach. Precision medicine is advancing significantly by leveraging insights into disease mechanisms, biological targets, and biomarkers to improve patient outcomes. Current clinical trials are exploring innovative approaches, such as genomic analysis in lung cancer, genotyping for response to opioid therapy, and identifying markers to prevent preterm birth. These efforts aim to personalize treatments by using big data and engineering to assess patient responses and develop targeted interventions. Beyond genomics, precision medicine integrates various scientific disciplines to create data-driven health strategies, with engineering playing a critical role in biomarker discovery, diagnostics, and drug delivery systems. |
| کلمات کلیدی | personalized medicine cancer prevention |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| IMG-20241201-WA0031.jpg | 1404/01/23 | 47050 | دانلود |
| abstract.docx | 1404/01/23 | 13968 | دانلود |
| program.pdf | 1404/01/23 | 1272954 | دانلود |
| invitation.jpg | 1404/01/23 | 123521 | دانلود |
| certificate.jpg | 1404/01/20 | 3468199 | دانلود |
