Early classification of data streams involves predicting the class label of a data stream before it is fully observed. This approach is particularly valuable in time-sensitive domains, such as the spread of fake news on socia...Read more
In this study, we aim to evaluate whether using information from medical reports for a large private dataset alongside small labeled datasets can lead to improved model performance. First, we introduce a pipeline to obtain a ...Read more
Recommender systems play a pivotal role in today's digital age, significantly improving the user experience by suggesting items or content that align with a user's preferences and behavior. In particular, sequential recommend...Read more
The fast growth of social networks and their data access limitations in recent years has led to increasing difficulty in obtaining the complete topology of these networks. However, diffusion information over these networks is...Read more
In recent years, the rapid development of high-throughput technologies has led to many types of omics data. Various methods have been proposed to instill biological insights from each data type. However, with the advancement ...Read more
According to the recent improvements in communications and interactions between computers and humans, the need of recognizing and classifying human emotions is felt more; But one of the challenges we confront is individual di...Read more
Increasing evidence from novel research demonstrates that circRNAs play a role in the onset and
development of various diseases. Recently, numerous computational methods have been
proposed to predict circRNA-disease associa...Read more
Breast cancer can be screened, diagnosed, and managed earlier with digital mammograms. Data shortages are one of the main challenges in many medical image processing tasks, including this one. There are only a limited number ...Read more
Despite the state-of-the-art performance of deep convolutional neural networks, they are susceptible to bias and malfunction in unseen situations. The complex computation behind their reasoning is not sufficiently human-under...Read more
Nowadays, nutrition and the food system are among the most important aspects
of daily life. In order to improve the performance of food recommendation systems, it would be beneficial to expand models that have a good underst...Read more
Compound-protein interaction (CPI) prediction, which determines the binding affinity of the interaction between a compound (drug candidate) and a target protein, plays a vital role in the drug discovery process. Experimentall...Read more
Novel drug discovery and development has extremely high costs and slow pace, which makes drug repurposing an attractive proposition because it involves the use of de risked compounds, with potentially lower overall developmen...Read more
The purpose of this research is to estimate the probability of message dissemination when data is incomplete. To achieve this, diffusion models and their application in estimating message transmission probabilities have been ...Read more
Expansion of the volume of available information has made it one of the most important issues today to access the information that each person wants in the fastest possible time. One of the solutions to this problem is the id...Read more
The problem of multi-object tracking, a.k.a MOT, is detecting multiple objects in consecutive video frames and properly tracking them in the whole video. Nowadays, MOT is widely used in various applications such as autonomous...Read more
Human visual attention is a mapping that determines to what regions of an image human’s eyes focus more while perceiving it. Personalized visual attention is visual attention computed for a specific individual. The importance...Read more
Personalization using machine learning methods in recommender systems has received a lot of attention in recent years. In practical issues, the data related to the transaction of users and items is usually sparse. Therefore, ...Read more
Parkinson's is a neurological disease that affects the function of different parts of the body. Despite the widespread effects of this disease on human motor functions and even decision-making, it is clear that it causes the ...Read more
The primary purpose of this project is to identify cancer-related genes using PPI networks and
machine learning and data representation models. We integrated the protein-protein
interaction (PPI) network with gene expressio...Read more
The numerical value of interaction in a protein-compound pair determines the tendency of a
compound (drug candidate) to bind to a target protein, which plays a key role in the initial phase
of the drug discovery process. In...Read more
Lately, the ASGE1 has addressed the resect and discard strategy known as PIVI2,
determining that if a polyp is less than 5mm, we can omit histopathological
examinations if we are highly confident with our diagnosis. PIVI al...Read more
Despite the recent advances of deep neural networks and achieving state-of-the-art perfor- mance in many fields, they are susceptible to bias and malfunction in unseen situations. The complex computation behind their reasonin...Read more
We have assessed this study to identify the elements that the promoters tend to interact with
them more than other regions in DNA, which is a sign that they might have a function in the
gene regulation process. We started s...Read more
In this project network of co-mutations in breast cancer has been analyzed. By
finding communities in co-mutational network groups of genes that are mutating together
significantly in breast cancer patients have been founde...Read more
DBS is used to manage some of the symptoms of Parkinson's Disease that cannot be adequately controlled with medications.[9][10] It is recommended for people who have PD with motor fluctuations and tremor inadequately controll...Read more
Clustered Regularly Interspaced Short Palindromic Repeats, or in short, CRISPR is a relatively new
technology that enables geneticists and medical researchers to edit parts of the genome by removing,
adding, or altering par...Read more
Many studies have identified cancer subtypes based on the cancer driver genes, or
the proportion of mutational processes in cancer genomes, however, none of these cancer subtyping
methods consider these features together to...Read more
During the past few years, self-supervised contrastive learning has emerged as a paradigm for deep learning. In terms of representation learning, self-supervised learning can be thought of as an unsupervised learning approach...Read more
The advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, resulting in the identification of many cancer-associated genes. Although cancers in a same tissue ...Read more
Single-cell imaging is a new technology that provides us information such as location, appearance, and biomarkers of the protein levels of each of the sample cells. For analytical use of the samples and comparing them with ea...Read more
Graphs are powerful tools for modeling real-world data. Data analysis using graphs allows us to study the samples relations and identify rich patterns. Although graph modeling can result in a better understanding of data, it ...Read more
Hi-C is a method for capturing contacts between all pairs of DNA fragments in one
experiment. In the process of Hi-C experiment, pairs of fragments appearing as ligation are
recorded as interactions. However, not all of the...Read more
Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths in the world. It has been reported that ∼10%-15% of individuals with colorectal cancer experience a causative mutation in the known susceptibility ...Read more
A large number of machine learning problems are considered as structured output problems in which the goal is to find the mapping function between an input vectors to a number of variables in the output side which are statist...Read more
Non-coding RNAs (ncRNAs) form a large portion of the mammalian genome. However, their biological functions are poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we analyze de novo somatic...Read more
