چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | ثمینا سلطانی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | کمیته تحقیقات دانشجویی |
| کد مقاله | 83800 |
| عنوان فارسی مقاله | مروری سیستماتیک از یادگیری ماشینی و رویکردهای یادگیری عمیق برای استفاده مجدد از دارو در بیماری آلزایمر |
| عنوان لاتین مقاله | New drugs? No, thank you! We have enough of them: A Systematic Review of Machine Learning and Deep Learning Approaches for Drug Repurposing in Alzheimer’s Disease |
| نوع ارائه | پوستر |
| عنوان کنگره / همایش | ۲۴ امین کنگره کشوری دانشجویان علوم پزشکی |
| نوع کنگره / همایش | بین المللی |
| کشور محل برگزاری کنگره/ همایش | Iran (Islamic Republic) |
| شهر محل برگزاری کنگره/ همایش | تهران |
| سال انتشار/ ارائه شمسی | 1402 |
| سال انتشار/ارائه میلادی | 2023 |
| تاریخ شمسی شروع و خاتمه کنگره/همایش | 1402/07/12 الی 1402/07/14 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://congressapp.ir/arcims24/ |
| آدرس علمی (Affiliation) نویسنده متقاضی | Student Research Committee, Tabriz university of medical science, Tabriz, Iran |
| نویسنده | نفر چندم مقاله |
|---|---|
| مرتضی قوجازاده | دوم |
| ثمینا سلطانی | اول |
| رها جابری | سوم |
| عنوان | متن |
|---|---|
| کلمات کلیدی | Artificial Intelligence, Alzheimer, drug discover, drug development |
| خلاصه مقاله | Background and Aim: Alzheimer’s disease (AD) is a neurodegenerative disorder marked by cognitive and behavioral impairment that may affect daily life. AD has already caught nearly 50 million people worldwide but there is still no proper cure for this condition and the available treatment only can help with the prevention of the disease’s progress. Due to the unknown pathogenesis of AD, drug development processes can be extremely challenging. While there is evidence based on the possibility of using repurposed drugs to treat AD. Drug repositioning aims to propose new indications for drugs that are already marketed for other conditions. According to a large amount of data for investigating drug repurposing, using Artificial Intelligence (AI) algorithms such as Machine Learning (ML) or Deep Learning (DL) can be helpful. Therefore, in this systematic review in silico studies that used ML or DL approaches for AD drug repurposing were investigated. Method: A comprehensive systematic literature search was conducted in electronic databases, including PubMed, Scopus, Embase, Web of Science, and Google Scholar, up to April 2023. Two independent reviewers evaluated the retrieved publications. All studies that used Machine Learning or Deep Learning to predict repurposed drug candidates for AD were included. Studies that met our inclusion criteria were then critically appraised by two authors independently. Data such as databases used in studies predicted medications, etc. were extracted. Results: We retrieved 276 relevant publications in electronic databases. After thoroughly examining the titles and abstracts and removing duplicates (n=108) 36 studies remained. Full texts of these articles were reviewed, and ultimately 33 studies were included. Most of the studies used neural networks to predict the drug-disease or drug-drug relation. while a few predict possible repurposing candidates by estimating drug-drug relations. Many of the studies used ML or DL algorithms to identify risky genes related to AD and predict possible candidates using their effect on these genes. Most of the studies used available databases such as PubChem and CHEMBL, etc. as a dataset but two studies used data mining of free texts in addition to usual databases. The reported drugs included a wide range of medications such as antiepileptics, diuretics, cardiovascular medication, etc. Studies used published data of their reported repurposed drugs as an effective medication to show their method’s accuracy. Conclusion: There is a need to investigate the efficacy of reported candidates with clinical or preclinical studies. Some of the predicted candidates have already been investigated by such studies. This proves the accuracy of ML or DL approaches in drug repurposing for AD. While there is no proper medication for this condition the complicated process of drug development using ML and DL to investigate drug repurposing candidates can be helpful to overcome Alzheimer’s disease. |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| 22.pdf | 1403/09/19 | 155465 | دانلود |
| 222.pdf | 1403/09/19 | 100229 | دانلود |
